Avaliação da performance no treino em jogos desportivos...

Eduardo André de Azevedo Abade

Avaliação da performance no treino em jogos

desportivos coletivos

Tese de Doutoramento em Ciências do Desporto

Orientador: Professor Doutor António Jaime da Eira Sampaio

Universidade de Trás-os-Montes e Alto Douro

Vila Real, 2014

ii

Eduardo André de Azevedo Abade

Avaliação da performance no treino em jogos

desportivos coletivos

O trabalho apresentado nesta dissertação foi suportado pela Fundação para a Ciência e

Tecnologia (Portugal) bolsa SFRH / BD / 74544 / 2010

Universidade de Trás-os-Montes e Alto Douro

Vila Real, 2014

Este trabalho foi expressamente elaborado

com vista à obtenção do grau de Doutor

em Ciências do Desporto de acordo com o

Decreto-lei 115/2013 de 7 de Agosto.

iii

“Se acha que a educação é cara, experimente a ignorância”

Derek Bok

iv

DEDICATÓRIA

Aos meus pais, Eduardo José Abade e Maria Antonieta Abade e irmão Tiago

Abade. Não há nada melhor que me pudessem ter dado que uma boa educação!

v

AGRADECIMENTOS / ACKNOWLEDGEMENTS

“A vida deve ser uma constante educação”! Mais uma etapa cumprida com o apoio

indispensável de professores, família e amigos. Para eles o meu sentido agradecimento.

Ao professor Jaime Sampaio pela orientação imaculada. Pela disponibilidade diária

(literalmente), pelo apoio, paciência, espírito crítico e rigor que tão bem o caracterizam.

Não há preço que pague os últimos 4 anos de educação profissional e pessoal que me

prestou. Pelos “ok”, “boa”, “excelente”, “gosto”, “não gosto”, “corrige”…o meu muito

obrigado. A viagem ainda agora começou, espero eu!

Ao Bruno Gonçalves pela preciosa e insubstituível participação neste trabalho. Pelas

horas e horas de conversa, debate, partilha de conhecimento e companheirismo. É difícil

explicar o caminho desde o primeiro “olá, então o que é que fazes aqui no laboratório?”

até hoje. De colega a amigo!

Ao Bruno Figueira e ao Diogo Coutinho pela colaboração em todo o processo, desde

o primeiro dia! O vosso apoio foi fundamental em todos os momentos, bons e menos

bons. Obrigado pela troca de ideias, experiências e conhecimentos. Obrigado pelas

insubstituíveis gargalhadas e brindes Amigos!

À Alexandra e aos professores Nuno Leite, Catarina Abrantes e José Vilaça pelo

contributo científico prestado na elaboração deste trabalho.

Ao professor Carlo Castagna pela fantástica experiência que me proporcionou em

Itália, pela atenção prestada e competência profissional. Agradeço igualmente a sua

colaboração científica na realização deste trabalho.

A todos os colegas (Sara, Nuno, Laura, Rui, Manuel) e professores (Luís Vaz, Vítor

Maçãs, Isabel Gomes, Paulo Vicente) do CreativeLab pela ajuda direta ou indireta que

prestaram na elaboração deste trabalho. Ao Tiago Oliveira um especial obrigado pelo

seu contributo...a pessoa mais apaixonada por Andebol que alguma vez conheci.

Obrigado pelas ideias andebolísticas que partilhaste comigo. Ainda nos vamos cruzar no

retângulo de jogo, como adversários ou colegas de equipa!

Aos professores Paulo Sá e Mário Santos pela total disponibilidade, paciência,

colaboração e apoio prestados durante o processo de recolha de dados. Mas acima de

tudo pela vossa amizade. A vós devo muito do que tenho conseguido alcançar. Temos

com certeza um portfólio de momentos desportivos para mais tarde recordar, mas as

verdadeiras memórias terão sempre os pés debaixo da mesa.

Aos jogadores da ADA/Maia ISMAI pelo irrepreensível contributo dado na realização

deste trabalho. Foram 8 anos de trabalho fantásticos, da base ao topo. É um orgulho

olhar para trás e ver o percurso trilhado até ao presente.

Ao professor Alberto Carvalho por me ter incutido a verdadeira paixão pelo treino

desportivo. Não me esquecerei nunca do passo acelerado e abraço que me deu no

vi

momento imediatamente após a defesa da tese de licenciatura. O “obrigado” nunca será

suficiente para agradecer o que tem feito por mim e pelas competências que me tem

transmitido. Obrigado por acreditar.

Ao professor João Paulo Barbosa por me ter ensinado o significado das palavras

“competência” e “empreendedorismo”. Em algum lado teria que estar escrito que seria

meu/nosso orientador do estágio pedagógico. Foi um dos anos mais marcantes da minha

formação académica. Obrigado por ter incentivado a leitura e procura do conhecimento.

Obrigado pelos fantásticos anos que passámos juntos no Andebol.

Aos treinadores José Carlos Ribas, Raquel Silva, Paulo Ribas e Susana Leal pela

troca de experiências proporcionada ao longo de anos. A vossa dedicação ao Andebol é

ímpar.

Às jogadoras do Maiastars, da formação às seniores, por estarem sempre disponíveis

para colaborar. Mas acima de tudo pelo que aprendi com vocês. Proporcionaram-me

aprendizagens e momentos inigualáveis.

Ao professor Nuno Montenegro pelos assertivos e sábios conselhos que me deu

durante o estágio pedagógico. Ainda hoje respeito alguns dos seus mandamentos.

Ao professor Rolando Freitas por ter acreditado no meu valor.

A todos os professores com quem me cruzei. Tive uma tremenda sorte em vos ter como

tutores. Aos meus alunos, porque a melhor maneira de aprender é ensinar.

A toda a minha família, Tios, Primos e Avós por tudo o que significam. Á minha Tia

Isabel pelo carinho sem limites que tem pelo seu sobrinho. Obrigado por tudo

madrinha!

À Filipa, a minha melhor amiga, confidente e companheira. Obrigado pelos constantes

sacrifícios, por estares sempre presente, pelas discussões saudáveis e construtivas…e

pelas fantásticas viagens. Obrigado pelo teu carinho insubstituível!

Ao Carlos, Fernando, Filipe e Tiago (ordem alfabética) pela vossa amizade! Porque

Amigos há poucos…vocês são “aqueles” e sabem-no porquê.

A todos os meus colegas de licenciatura. Pelo que aprendi com vocês e pelos momentos

inesquecíveis que proporcionaram.

A todos aqueles que por lapso não estão aqui mencionados mas que contribuíram de

uma ou outra forma para a conclusão deste trabalho.

vii

RESUMO

O planeamento a curto prazo em jogos desportivos coletivos representa um desafio para

os treinadores, uma vez que o microciclo semanal inclui sessões de treino com objetivos

múltiplos. A necessidade de manter ou melhorar a capacidade física, o desenvolvimento

das habilidades técnicas e o treino tático, convergem numa complexidade de conteúdos

que requer conhecimentos profundos acerca das suas interações, no sentido de otimizar

a periodização e o planeamento do treino. Neste sentido, conhecer os perfis de carga

externa e interna dos jogadores torna-se imprescindível para um planeamento dirigido à

melhoria da performance desportiva.

Uma vez que o treino técnico-tático é incapaz de induzir adaptações neuromusculares

significativas, a primeira parte deste estudo procurou descrever os efeitos agudos que a

adição de sessões específicas de treino de força teve na resposta física, fisiológica e

performance técnico-tática em sessões de treino de Andebol. O treino de força mostrou-

se influenciador da intensidade do esforço durante a prática dos jogos reduzidos. Os

jogadores passaram mais tempo em zonas elevadas de frequência cardíaca quando

existiu treino de força antecedente. Em sessões de treino com jogos reduzidos 6x6, o

treino de força mostrou-se útil no aumento da intensidade do esforço, não deteriorando a

capacidade de salto. Mesmo antecedendo jogos reduzidos 3x3, o treino de força

promoveu aumentos do tempo passado em zonas elevadas de frequência cardíaca,

assumindo-se como uma ferramenta apropriada para o desenvolvimento da performance

aeróbia em contexto de jogo. No entanto, os treinadores deverão considerar a

possibilidade da ocorrência de mais falhas técnicas e diminuição da eficácia no remate

quando o treino de força antecede sessões de jogos reduzidos com um menor número de

participantes.

A segunda parte desta tese focou-se na avaliação da carga externa durante unidades de

treino de futebol, através da descrição de perfis de performance e métodos de

classificação dos jogadores. Aparentemente, a elevada variabilidade de estímulos é uma

característica transversal às sessões de treino de equipas jovens de elite (sub-15/17/19).

O foco no desenvolvimento de princípios táticos básicos e habilidades técnicas em

idades mais jovens (sub-15) parece diminuir o estímulo fisiológico. Por outro lado, à

medida que a idade biológica avança, os treinadores parecem privilegiar mais situações

de jogo, o que resulta num aumento significativo da intensidade do treino. Esta

viii

tendência foi mais evidente nas unidades de treino de escalões sub-17, constituídas por

jogos reduzidos com poucos constrangimentos que induziram valores mais elevados de

distâncias totais e distâncias percorridas em sprint. Em idades mais avançadas (sub-19),

as interrupções e feedbacks recorrentes da crescente preocupação com os modelos

táticos das equipas parece comprometer o padrão fisiológico competitivo. Esta

descrição dos perfis físicos e fisiológicos foi ainda utilizada para classificar os jogadores

em grupos distintos de performance, em detrimento de critérios comuns como a idade e

posto específico. O estabelecimento de grupos homogéneos reduziu a variabilidade na

resposta ao estímulo, o que permite aos treinadores um controlo mais eficiente das

respostas às cargas de treino.

Palavras-chave: Planeamento a curto prazo; carga interna; carga externa; treino de

força; jogos reduzidos; perfis de performance; andebol; futebol.

ix

ABSTRACT

Short-term planning in team sports is challenging for coaches, since the weekly training

cycles include sessions with multiple goals. The need to maintain or improve the

physical capacity, the development of technical skills and tactical training, represent a

complexity of contents that require a significant knowledge of its interactions in order to

optimize the training processes. In this sense, studying the players’ internal and external

loads profiles is a key issue to establish training programs aimed for the improvement of

sports performance. Technical and tactical training do not induce significant

neuromuscular adaptations. For that reason, the first part of this study described the

acute effects of specific strength training sessions in the physical, physiological,

technical and tactical response during handball small sided games. It was showed that

strength training influenced the intensity of the effort during small sided games. The

players spent more time in higher heart rate zones when there was precedent strength

training. In training sessions that included 6x6 small sided games, strength training was

able to increase training intensity without impairing the vertical jump capacity. Even

when strength training preceded 3x3 small sided games, players experienced more time

in higher heart rate zones. Thus, strength training may be used as an appropriate tool to

develop the aerobic performance in game context. However, coaches should consider

the occurrence of a higher number of technical errors and the deterioration of the shots

efficiency when strength training precedes small sided games with a lower number of

players.

The second part of this thesis focused on the evaluation of the external load during

football training units, using the description of performance profiles and methods of

classifying the players. Apparently, the high variability of stimuli is a key characteristic

of elite young football training sessions (sub-15/17/19). The focus on the development

of basic tactical principles and technical skills in younger ages (sub-15) seems to

decrease the physiological stimulus. On the other hand, as the biological age increases

coaches seem to privilege more game situations, which results in higher training

intensities. This trend was clearer in sub-17 training units that included small sided

games with fewer constraints, inducing higher values of total distances and distances

covered in sprint. In older ages (sub-19), the focus on team tactical principles appears to

require additional coaching intervention, promoting more interruptions and

compromising the replication of the competitive physiological pattern. This description

x

of the physical and physiological profiles was also used to classify the players in

different groups of performance, contrasting the traditional criteria of classification

based on age and specific playing position. The establishment of homogenous groups

reduced the variability of the response to stimuli, allowing coaches to have a more

accurate and efficient control on the players’ responses to training loads.

Key words: Short-term planning; internal load; external load; strength training; small

sided games; performance profiles; handball; football.

xi

LISTA DE PUBLICAÇÕES E COMUNICAÇÕES

Durante a elaboração desta tese, alguns trabalhos foram publicados, aceites ou

submetidos para publicação em revistas indexadas (ISI) com sistema de arbitragem.

Algumas partes integrantes ou derivadas da tese foram apresentadas em congressos,

publicadas em livros de resumos e em edições especiais de jornais científicos. Foi

também realizada uma visita de investigação.

Artigos em revistas indexadas no ISI com sistema de arbitragem, como primeiro

autor

Abade E, Gonçalves B, Leite N and Sampaio J (2013). Time-motion and physiological

profile of football training sessions performed by under 15, under 17 and under 19 elite

Portuguese players. International Journal of Sports Physiology and Performance.

(Acceptance Date: June 27, 2013, Impact factor = 2.3)

Abade E, Abrantes C, Ibañez J and Sampaio J (Under Review). Acute effects of

strength training in the physiological and perceptual response in handball small-sided

games.

Abade E, Gonçalves B, Vilaca J and Sampaio J (Under Review). Acute effects of

different strength training programs on the vertical jump and technical actions in

handball small-sided games during preseason.

Abade E, Gonçalves B, Silva A, Leite N, Castagna C and Sampaio J (Submitted).

Helping coaches to classify young footballers according to their training performances.

Artigos em revistas indexada no ISI com sistema de arbitragem, como co-autor

Oliveira T, Abade E, Gonçalves B and Sampaio J (Submitted). Physical and

physiological profiles of elite handball players during training sessions and friendly

matches according to playing positions.

xii

Resumos publicados em livros de atas de encontros técnico-científicos

Abade E, Oliveira T, Gonçalves B & Sampaio J (2013). Strength and conditioning for

team sports: an update. Atas do 3º Simpósio Internacional de Força e Condição Física.

ISBN: 978-989-704-142-6

Comunicações orais em congressos técnico-científicos

Abade E (2013). Strength and conditioning for team sports: an update. 3º Simpósio

Internacional de Força e Condição Física. Universidade de Trás-os-Montes e Alto

Douro, Vila Real.

Abade E (2013). Metodologias de treino – novas perspetivas. 4º Congresso

Internacional Handball Project, “Pensar o Andebol em 2030”. Maia, Portugal.

Abade E (2013). Importância e organização do treino de força para performances

desportivas de excelência. Seminário de investigação nos jogos desportivos coletivos.

Universidade de Trás-os-Montes e Alto Douro, Vila Real.

Abade E (2012). Efeitos agudos do treino de força em jogos reduzidos. Seminário

Brainstorming – fundamentos e aplicações à investigação nos jogos desportivos

coletivos. Universidade de Trás-os-Montes e Alto Douro, Vila Real.

Abade E (2012). Efeitos do treino de força e jogos reduzidos na carga de treino em

jogadores de Andebol. VI Seminário técnico-científico da Federação Portuguesa de

Andebol. Maia, Portugal.

Abade E (2012). Treino de potência para jogadores de Andebol. VI Seminário técnico-

científico da Federação Portuguesa de Andebol. Maia, Portugal.

Abade E (2012). A importância do treino de força na prevenção de lesões. VI

Seminário técnico-científico da Federação Portuguesa de Andebol. Maia, Portugal.

Visitas de investigação

FIGC, Settore Tecnico Coverciano – Laboratorio di metodologia dell’allenamento e

biomeccanica applicata al calcio. Federação Italiana de Futebol (FIGC). Coverciano,

Florença, Itália (2013).

xiii

OUTRAS PUBLICAÇÕES

Outros trabalhos foram desenvolvidos paralelamente à elaboração desta tese, como

primeiro ou co-autor.

Artigos em revistas indexada no ISI com sistema de arbitragem, como co-autor

Carvalho A, Caserotti P, Carvalho C, Abade E and Sampaio J (2013). Reliability of

concentric, eccentric and isometric knee extension and flexion with the REV9000

isokinetic dynamometer. Journal of Human Kinetics.

Vaz L, Abade E, Fernandes H and Reis V (2013). Cross-training in rugby: a review of

research and practical suggestions. International Journal of Performance Analysis in

Sport.

Azevedo R, Mourão P, Abade E and Carvalho A (Under Review). Is it important to

know the load mass in lifting tasks to prevent falls?

Carvalho A, Caserotti P, Carvalho C, Abade E and Sampaio J (Under Review). Effects

of a short time concentric versus eccentric training in electromyography activity and

peak torque of quadriceps.

Carvalho A, Mourao P and Abade E (Under Review). Effects of strength training

combined with specific plyometrics on body composition, vertical jump height and

lower limb strength development in elite male handball players: a case study.

Carvalho A, Carvalho C, Caserotti P, Abade E and Sampaio J (submitted). Effects of a

short-time concentric versus eccentric training and detraining in the peak torque of

quadriceps and hamstrings.

Carvalho A, Abade E, Carvalho C and Sampaio J (Submitted). Reliability of

Electromyography and peak torque during maximum voluntary concentric, isometric

and eccentric contractions of quadriceps muscles in healthy subjects.

Resumos publicados em livros de atas de encontros técnico-científicos

Carvalho A, Mourão P, Resende R, Abade E. and Carvalho C (2013). Comparison of

anthropometric profiles between different senior male Volleyball competition levels:

xiv

national team, first and second Portuguese divisions. 18th

annual Congress of the

European College of Sport Science. Barcelona, Spain. ISBN: 978-84-695-7786-8.

Carvalho C, Mourão P, Sá P, Abade E and Carvalho A (2013). Comparison of

anthropometric profiles between different senior male Basketball competition levels:

first, second and third Portuguese divisions. 18th

annual Congress of the European

College of Sport Science. Barcelona, Spain. ISBN: 978-84-695-7786-8

Mourão P, Abade E, Martins D, Gonçalves F, Carvalho A and Viana J (2012).

Effectivness of a neuromuscular and proprioceptive combination training program in

preventing injuries in youth soccer players. In International Seminar on Physical

Activity and Related Injuries. University of Trás-os-Montes e Alto Douro, Vila Real.

Acta Med Port, 25, 9. ISSN:0870-399X, e-ISSN:1646-0758

Carvalho A, Abade E, Carvalho C and Mourão P (2012). Is isokinetic conventional

ratio “Hcc:Qcc” a good indicator of injury?. In International Seminar on Physical

Activity and Related Injuries. University of Trás-os-Montes e Alto Douro, Vila Real.

Acta Med Port, 25, 8. ISSN:0870-399X, e-ISSN:1646-0758

Comunicações poster em congressos técnico-científicos

Carvalho A, Mourão P, Resende R, Abade E and Carvalho C (2013). Comparison of

anthropometric profiles between different senior male Volleyball competition levels:

national team, first and second portuguese divisions. 18th

annual Congress of the

European College of Sport Science. Barcelona, Spain.

Figueira B, Gonçalves B, Coutinho D, Abade E, Freitas R, Leite N, and Sampaio J

(2013). O perfil físico e fisiológico da competição pode classificar jovens futebolistas!

8º Seminário de Desenvolvimento Motor da Criança. Universidade de Trás-os-Montes e

Alto Douro, Vila Real.

Sá P, Carvalho A and Abade E (2013). O jogador especialista na defesa de Andebol. 2º

Congresso internacional de treino desportivo. Instituto superior da Maia. Maia,

Portugal.

Carvalho C, Mourão P, Sá P, Abade E and Carvalho A (2013). Comparison of

Anthropometric Profiles between different senior male Basketball competition levels:

xv

first, second and third Portuguese divisions. 18th

annual Congress of the European

College of Sport Science. Barcelona, Spain.

Sá P, Carvalho A and Abade E (2013). Análise e preponderância do contra-ataque no

jogo de Andebol. 2º Congresso internacional de treino desportivo. Instituto superior da

Maia. Maia, Portugal.

Coutinho D, Gonçalves B, Figueira B, Abade E, Oliveira T, Maçãs V, and Sampaio J

(2013). Variação do perfil físico e fisiológico de jovens futebolistas ao longo de uma

competição concentrada. 8º Seminário de Desenvolvimento Motor da Criança.

Universidade de Trás-os-Montes e Alto Douro, Vila Real.

Abade E, Silva B, Santos F and Sá P (2012). Strength training methodologies applied to

elite handball teams. 9º Congresso técnico-científico de Andebol. Universidade

Lusófona, Lisboa, Portugal.

Carvalho A, Mourão P, Abade E and Carvalho C (2012). Power and explosive strength

comparison between men volleyball national team players. 8th

International Conference

on Strength Training. Norwegian School of Sport Sciences. Oslo, Norway.

Mourão P, Abade E, Martins D, Gonçalves F, Carvalho A and Viana J (2012).

Effectivness of a neuromuscular and proprioceptive combination training program in

preventing injuries in youth soccer players. Physical activity and related injuries

international seminar. University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.

Carvalho A, Abade E, Carvalho C and Mourão P (2012). Is isokinetic conventional

ratio “Hcc:Qcc” a good indicator of injury?. Physical activity and related injuries

international seminar. University of Trás-os-Montes e Alto Douro, Vila Real, Portugal.

Carvalho A, Abade E, Mourão P and Carvalho C (2012). Efeitos de um programa de

treino de força combinado com pliometria específica na composição corporal, impulsão

vertical e força dos membros inferiores em jogadores seniores de andebol. Congresso

internacional de treino desportivo. Instituto Superior da Maia, Portugal.

Carvalho A, Mourão P and Abade E (2012). Comparação da força explosiva e reativa

entre atletas pertencentes à seleção nacional masculina de voleibol. Congresso


Silva B, Abade E, Santos F and Sá P (2012). Scouting no Andebol. Congresso


xvi

Santos F, Abade E, Silva B and Sá P (2012). O modelo de jogo numa equipa de

Andebol. Instituto Superior da Maia, Portugal.

Comunicações orais em congressos técnico-científicos

Oliveira T, Abade E, Gonçalves B and Sampaio J (2013). Physical and physiological

profiles of youth elite handball players during training sessions and friendly matches

according to playing positions. 10º congresso técnico-científico da Federação

Portuguesa de Andebol, Universidade Lusófona, Lisboa.

xvii

ÍNDICE

DEDICATÓRIA IV

AGRADECIMENTOS / ACKNOWLEDGEMENTS V

RESUMO VII

ABSTRACT IX

LISTA DE PUBLICAÇÕES E COMUNICAÇÕES XI

LISTA DE TABELAS XX

LISTA DE FIGURAS XXI

CAPÍTULO 1 23

1.1. INTRODUÇÃO 24

1.1.1. A COMPLEXIDADE NOS JOGOS DESPORTIVOS COLETIVOS 24

1.1.2. MODIFICAR O CONTEXTO PARA OTIMIZAR A APRENDIZAGEM 25

1.1.3. COMO CONTEMPLAR A COMPLEXIDADE NO TREINO DOS JOGOS DESPORTIVOS

COLETIVOS? 28

1.1.4. DIMENSÕES DOS JOGOS REDUZIDOS 30

1.1.4.1. Dimensão muscular 32

1.1.4.2. Dimensão energética 36

1.1.4.3. Dimensão técnico-tática 38

1.1.5. PLANEAMENTO A CURTO PRAZO NOS JOGOS DESPORTIVOS COLETIVOS 43

1.1.5.1. Efeitos agudos do treino de força nos perfis de performance de andebolistas 43

1.1.5.2. Variabilidade nos perfis de resposta de jovens futebolistas às cargas de treino 49

1.2. OBJETIVOS E HIPÓTESES 52

1.3. REFERÊNCIAS 53

CAPÍTULO 2 71

2.1 ACUTE EFFECTS OF STRENGTH TRAINING IN THE PHYSIOLOGICAL AND

PERCEPTUAL RESPONSE IN HANDBALL SMALL-SIDED GAMES 72

2.1.1 ABSTRACT 72

2.1.2 INTRODUCTION 73

xviii

2.1.3 METHODS 75

2.1.3.1 Subjects 75

2.1.3.2 Design 75

2.1.3.3 Methodology 76

2.1.3.4 Statistical Analysis 77

2.1.4 RESULTS 77

2.1.5 DISCUSSION 79

2.1.6 CONCLUSION 82

2.1.7 REFERENCES 83

CAPÍTULO 3 88

3.1. ACUTE EFFECTS OF STRENGTH TRAINING PROGRAMS ON THE

VERTICAL JUMP AND TECHNICAL ACTIONS IN HANDBALL DURING

PRESEASON 89

3.1.1. ABSTRACT 89

3.1.2. INTRODUCTION 90

3.1.3. METHOD 92

3.1.3.1. Participants 92

3.1.3.2. Procedures 92

3.1.3.3. Measures 94

3.1.3.4. Analysis 94

3.1.4. RESULTS 95

3.1.5. DISCUSSION 99

3.1.6. REFERENCES 104

CAPÍTULO 4 107

4.1. TIME-MOTION AND PHYSIOLOGICAL PROFILE OF FOOTBALL TRAINING

SESSIONS PERFORMED BY UNDER 15, UNDER 17 AND UNDER 19 ELITE

PORTUGUESE PLAYERS 108

4.1.1. ABSTRACT 108


4.1.3. METHODS 110

4.1.3.1. Subjects 110

4.1.3.2. Design 111

4.1.3.3. Methodology 111

xix

4.1.3.4. Statistical Analysis 112

4.1.4. RESULTS 113


4.1.6. PRACTICAL APPLICATIONS 118

4.1.7. CONCLUSION 118


CAPÍTULO 5 123

5.1. HELPING COACHES TO CLASSIFY YOUNG FOOTBALLERS ACCORDING

TO THEIR TRAINING PERFORMANCES 124

5.1.1. ABSTRACT 124


5.1.3. METHOD 127

5.1.3.1. Participants 127

5.1.3.2. Procedures 128

5.1.3.3. ANALYSIS 129

5.1.4. RESULTS 130



CAPÍTULO 6 140

6.1. CONCLUSÕES E APLICAÇÕES PRÁTICAS 141

xx

LISTA DE TABELAS

Table 2.1. Comparing the time spent in HR zones and RPE values according to

the number of players and type of ST. .................................................................. 78

Table 3.1. Chronological schedule that preceded the protocol application .......... 93

Table 3.2. Analysis of Variance to Assess Differences in Vertical Jump

Performance by Number of Players in Small-sided Games, Type of Strength

Training, and Time of Testing. ............................................................................. 97

Table 3.3. Analysis of Variance to Assess Statistical Differences in % of

Technical Actions by Number of Players in Small-sided Games, Type of Strength

Training and Half (only statistical significant differences are presented). ........... 99

Table 4.1. Description of players’ sub-samples. ................................................ 110

Table 4.2. Analysis of distance covered, sprint characterization and body impacts

across age groups. ............................................................................................... 113

Table 4.3. Mean intersection Coefficient of variation (%) according to the age

groups. ................................................................................................................. 115

Table 5.1. Characterization of the cluster groups. .............................................. 130

xxi

LISTA DE FIGURAS

Figura 1.1. Modelo de interação de constrangimentos (Newell, 1986)......................... 26

Figura 1.2. Aspetos do treino cognitivo a considerar para a construção de tarefas de

treino (Fajardo, 1999). .................................................................................................... 28

Figura 1.3. Exemplo de um exercício que contempla a colaboração e oposição

característica dos desportos de equipa. Em função da atuação do defensor, o atacante

deve escolher entre o lançamento ou progressão com bola (Fajardo, 1999). ................. 29

Figura 1.4. Mudanças na resposta da capacidade força em 3 tipos de treino. Os registos

dos grupos do treino de força e treino de força + resistência foram semanais. O grupo do

treino de resistência foi avaliado no início e final do protocolo (Hickson, 1980). ......... 33

Figura 1.5. Valores médios (%FC máxima) da intensidade do exercício em diferentes

situações de treino de futebol (Hill-Haas et al., 2011). .................................................. 36

Figura 1.6. Abordagem a sistemas complexos utilizada para análise da performance

desportiva (Hughes & Franks, 2004). ............................................................................. 39

Figura 1.7. Duas dimensões da análise do jogo (Volossovitch, 2008). ......................... 40

Figura 1.8. Média ± SD de contactos com a bola em jogo 4x4 e 8x8 de futebol (Jones &

Drust, 2007). ................................................................................................................... 42

Figura 1.9. Os principais fatores responsáveis por determinar o resultado desportivo

(Verkhoshansky, 2006). .................................................................................................. 43

Figura 1.10. Modelo de treino “dois fatores”. O efeito imediato de uma sessão de TF é

caracterizado pelo somatório de dois processos: ganhos na aptidão física e fadiga

(Zatsiorsky & Kraemer, 2006)........................................................................................ 45

Figura 1.11. Intensidade do exercício (% FCmax) em vários formatos de jogos

reduzidos de futebol (Hill-Haas, Dawson, Coutts, & Rowsell, 2009). .......................... 48

Figure 2.1. ST x HR ZONE interaction to the time spent in each one of the four HR

zones (a); PLAYERS x ST x HR ZONE interaction to the time spent in each one of the

four HR zones (b 3x3, b 6x6); PLAYERS x ST interaction to RPE values (c). ............ 79

xxii

Figure 3.1. Results from interaction Players x Strength Training x Time for squat jump

values. LOWER (lower limbs strength training); POS SSG (after small sided games);

POS ST (after strength training); PRE ST (before strength training); TOTAL (upper and

lower limbs strength training); UPPER (upper limbs strength training). ....................... 96

Figure 3.2. Results from interaction Players x Strength Training x Time for counter

movement jump values. LOWER (lower limbs strength training); POS SSG (after small

sided games); POS ST (after strength training); PRE ST (before strength training);

TOTAL (upper and lower limbs strength training); UPPER (upper limbs strength

training). ......................................................................................................................... 96

Figure 3.3. Results from interaction Players x Strength Training x Time for abalakov

jump values. Legend: LOWER (lower limbs strength training); POS SSG (after small



training). ......................................................................................................................... 97

Figure 3.4. Percentage (%) of the height variation from the baseline (PRE ST) to the

interaction Players x Strength Training x Time.............................................................. 98

Figure 4.1. Results from distance covered for each speed zone (a), time spent in each

heart rate zone (b), number of impacts for each intensity zone (c) and distance in

different intensity zones for each 100m covered at very low intensity (d). ................. 115

Figure 5.1. Distribution (%) of players in each cluster considering the players’

development stage and playing position ....................................................................... 131

Figure 5.2. Results from distance covered for each speed zone (i), number of impacts

for each intensity zone (ii) time spent in each heart rate zone (iii) and predictor

importance to all considered variable (iv). Significant differences are identified as: (a)

Cluster 1 vs. Cluster 2; (b) Cluster 1 vs. Cluster 3; (c) Cluster 2 vs. Cluster 3 ............ 132

Figura 6.1. Representação esquemática das principais aplicações práticas (resultados do

presente trabalho).………………………………………………………………….....144

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CAPÍTULO 1

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1.1. INTRODUÇÃO

1.1.1. A complexidade nos jogos desportivos coletivos

A essência dos jogos desportivos coletivos (JDC) consiste na imprevisibilidade dos seus

acontecimentos (Glazier, 2010), resultado do grande número de possibilidades de

escolha no decurso de cada jogo, que são únicas e exigem uma adaptação constante dos

jogadores e das equipas. O número de jogadores, as relações que se estabelecem entre

eles, a diversidade de opções que cada um pode tomar e a sua incerteza comportamental

contribuem para que a natureza dos JDC seja complexa (Balague, Torrents, Hristovski,

Davids, & Araujo, 2013).

A complexidade pode ser entendida como uma medida de número de possibilidades

(Bar-Yam, 2003), que no âmbito técnico, tático, físico, psicológico e social dos JDC se

interligam mutuamente (Volossovitch, Dumangane, & Rosati, 2010). Assim, a

complexidade faz apelo à estratégia, ou seja, à arte de utilizar informações que surgem

durante a ação, integrá-las e formular esquemas capazes de reunir o máximo de certezas

para defrontar o incerto (Morin, 1992). Apesar do equilíbrio, desequilíbrio, organização,

interação e a incerteza serem características da complexidade, esta não significa

obrigatoriamente desordem (Volossovitch et al., 2010). Um dos princípios da

complexidade, o da auto-organização, descreve que todos os seres vivos são sistemas

dotados de grande complexidade, fruto da riqueza de interações entre as suas partes

constituintes (Bauer, 1999). Este princípio sublinha que tais sistemas são capazes de

resistir às perturbações externas e tirar partido delas para aprenderem e se

reorganizarem (Duarte, Araújo, Correia, & Davids, 2012).

No âmbito dos JDC, os jogadores deverão ser capazes de gerir a desordem resultante

dos constrangimentos decorrentes do jogo, de se adaptar e auto-organizar de forma

dinâmica (McGarry, Anderson, Wallace, Hughes, & Franks, 2002), tomando decisões

adequadas às circunstâncias vigentes e que respeitem o ambiente que as envolve (Bauer,

1999). Assim, a performance nos JDC deve ser o resultado de um processo de treino a

longo prazo que prepare os jogadores para a complexidade que a competição exige

(Sampaio & Maçãs, 2012). Mais, o treino deve estar direcionado para as ações

funcionais, ajustadas ao contexto e orientadas para um objetivo, devendo ser mais

caracterizadas pela eficácia do que pela sua estética (Araujo, Travassos, & Vilar, 2010).

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Toda a complexidade do processo de jogo pode ser confundida com o comportamento

caótico, que é caracterizado pela sensibilidade às condições iniciais e às pequenas

perturbações. Na sua essência, caos refere-se ao fenómeno a partir do qual os sistemas

compostos por partes que se relacionam, cada uma das quais com as suas próprias

regras de comportamento, podem gerar interações e efeitos não lineares e de certa forma

imprevisíveis (Holbrook, 2003). Assim, o comportamento de um sistema é altamente

influenciado por variações mínimas que podem ocorrer no seu estado inicial, tornando-

se o seu desfecho impossível de prever (Gleick, 1987). A título de exemplo prático: um

guarda-redes de Andebol ou Futebol pode optar por fazer a reposição de bola para o

jogador A ou B. A decisão de passar a bola para o jogador A pode hipoteticamente

determinar o sucesso na concretização do processo ofensivo, que por sua vez pode

significar a vitória no jogo, a conquista do campeonato e o apuramento para uma

competição internacional. Por outro lado, o passe para o jogador B poderia resultar na

perda de posse de bola e consequente insucesso.

O jogo traduz-se numa sequência de eventos organizada de forma catastrófica e que

oscila entre períodos de relativa estabilidade e previsibilidade e acontecimentos

casuísticos geradores de desequilíbrios e do imprevisto (Volossovitch et al., 2010).

Como consequência, o jogo deve ser interpretado de forma dinâmica e auto-organizada

para que se percebam os comportamentos emergentes dos jogadores inseridos num

ambiente ecológico (Gonçalves, Figueira, Maçãs, & Sampaio, 2013). Desta forma, a

análise das interações entre os jogadores e a identificação dos padrões de jogo

emergentes poderão preservar a normal sequência do jogo (Vilar, Araújo, Davids, &

Button, 2012).

1.1.2. Modificar o contexto para otimizar a aprendizagem

O processo de aquisição de skills motores e desportivos tem sido alvo de várias

abordagens teóricas. As teorias mais analíticas estão direcionadas para a psicologia

cognitiva e defendem que a prática repetida ao longo do tempo leva à memorização de

padrões motores estanques (Davids, Araújo, & Shuttleworth, 2005). Por exemplo, a

teoria do processamento de informação defende que a regulação das ações reside na

existência de programas motores genéricos armazenados no sistema nervoso que

especificam o modelo ideal de execução (Temprado & Laurent, 1999). Ao atribuir

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grande importância aos processos internos do sujeito, a teoria do processamento de

informação desloca o problema da tomada de decisão para uma estrutura interna pré

existente e negligencia o ambiente que envolve a tomada de decisão do jogador (Araujo,

Davids, & Serpa, 2005).

Assim, o controlo da ação deve ser percetivo e não assente numa elevada complexidade

de processos computacionais ou da memória (Shaw, 2003). É neste âmbito que surge a

perspetiva eco-dinâmica da aprendizagem, que refuta os modelos tradicionais e defende

que as ações não são impostas por uma estrutura pré-existente, mas residem no sistema

sujeito-ambiente (Gibson, 1979). De entre os vários fatores capazes de influenciar o

comportamento do sujeito nesse ambiente, destacam-se a estrutura e a física do

envolvimento, a biomecânica do corpo de cada indivíduo, a informação percetual

relativa às variáveis informacionais e as exigências específicas de cada tarefa (Warren,

2006) (ver figura 1.1). Assim, os desportistas peritos distinguem-se pela capacidade de

encontrar as informações que, de acordo com as várias possibilidades, lhes permitem

atingir o seu objetivo (Araujo et al., 2005).

Figura 1.1. Modelo de interação de constrangimentos (Newell, 1986).

No entanto, a perspetiva eco-dinâmica não deve ser considerada de forma isolada

(Araujo et al., 2010), uma vez que determinados padrões coordenados podem emergir

entre as partes do sistema de movimento dinâmico através de um processo de auto

organização (Davids, Button, Araujo, Renshaw, & Hristovski, 2006). O processo de

treino não deve ser caracterizado por estímulos e respostas constrangidas por regras pré-

definidas cognitivamente pelo jogador, mas sim pela organização funcional de

atividades práticas (Araujo, Davids, & Hristovski, 2006). Cabe assim ao treinador

perceber quais os constrangimentos mais adequados a cada situação e de que forma é

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que eles influenciam essa organização funcional (Passos, Araujo, Davids, &

Shuttleworth, 2008).

Durante as sessões de treino, os treinadores podem e devem recorrer a múltiplos

parâmetros de ensino que proporcionem a prática de diferentes movimentos e permitam

aos jogadores criarem uma base de experiências que os possa ajudar a construir variados

esquemas de comportamentos (Schmidt & Lee, 1999). No treino de remate de Andebol,

por exemplo, os esquemas utilizados devem incluir o maior número possível de

combinações que exijam mudanças em vários comportamentos com vista à otimização

do gesto técnico (Wagner & Muller, 2008). Respeitando este princípio, o jogador

assimila informação que o ajudará a alterar e ajustar os seus comportamentos em função

de diferentes condições e contextos. No caso particular do remate no Andebol, os

pressupostos para o desenvolvimento deste gesto técnico sugerem que o treino deve

variar parâmetros como velocidade de execução, ponto de largada da bola, ângulo do

braço no remate e facilitação ou handicap da impulsão vertical (Roth, 1989). Assim

como no futebol, onde manipular e constranger gestos técnicos como receção, drible e

remate já mostrou ser benéfico na não-linearidade da aprendizagem e na criação de

padrões de movimentos funcionais durante a prática (Schöllhorn, Hegen, & Davids,

2012). A manipulação destes parâmetros torna os sistemas instáveis e fá-los auto

organizarem-se (Wagner & Muller, 2008), oferecendo ao sujeito a capacidade de reagir

continuamente a novas situações de forma rápida e adequada (Schollhorn, Mayer-Kress,

Newell, & Michelbrink, 2009).

Neste âmbito, o treino diferencial garante a variabilidade da qualidade e quantidade dos

estímulos de exercício para exercício (Schöllhorn et al., 2012), estimulando o jogador a

adaptar-se e a criar uma variedade de padrões de comportamento (Frank, Michelbrink,

Beckmann, & Schollhorn, 2008). A abordagem diferencial tira partido das flutuações

num sistema complexo aumentando-as através de uma “não repetição” e constante

mudança nas tarefas, o que acrescenta perturbações estocásticas (Schöllhorn et al.,

2012). Assim, as flutuações nos subsistemas do sujeito são exploradas mesmo durante a

aprendizagem, aportando-lhe a capacidade de ele próprio encontrar padrões de

performance dependentes do contexto em que está inserido (Frank et al., 2008).

Baseados nestes pressupostos, os jogos reduzidos (JR) assumem-se como uma

ferramenta útil no processo de treino, permitindo ao treinador manipular uma série de

variáveis que influenciam os estímulos dos exercícios, tais como a área de jogo, número

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de jogadores, feedback do técnico, regime intervalado ou contínuo, regras e uso de

guarda-redes (Hill-Haas, Dawson, Impellizzeri, & Coutts, 2011). As vastas

possibilidades de constrangimentos aplicados aos JR facilitam o desenvolvimento de

habilidades técnico-táticas e melhoria da capacidade física em contexto apropriado de

jogo (Little, 2009).

1.1.3. Como contemplar a complexidade no treino dos jogos desportivos coletivos?

As abordagens teóricas ao treino dos JDC têm sofrido alguns avanços que se opõem aos

modelos mais clássicos, que privilegiavam a simplificação do jogo em elementos

isolados, que desconsideravam a sua totalidade complexa e desrespeitavam as suas

inter-relações (Reverdito & Scaglia, 2007). Os JDC são férteis em acontecimentos cuja

complexidade não pode ser prevista antecipadamente, exigindo aos jogadores uma

predisposição estratégica e tática permanentes (McGarry, 2009). Assim, a definição de

objetivos e seleção de exercícios para o treino não deverá ir de encontro à

automatização do gesto através de repetições indeterminadas, porque embora o jogador

possa ir ajustando a execução desse mesmo gesto, não terá um suporte motor

suficientemente amplo para dar a resposta ideal numa qualquer situação competitiva,

que nunca se repete da mesma maneira (Schollhorn et al., 2009). Para que os jogadores

desenvolvam os seus processos cognitivos e sejam capazes de se adaptar aos diversos

cenários competitivos, é necessário atribuir estímulos variados no treino (ver figura 1.2)

em que o jogador procure a resposta ideal de acordo com o contexto e as suas

características (Fajardo, 1999).

Figura 1.2. Aspetos do treino cognitivo a considerar para a construção de tarefas de

treino (Fajardo, 1999).

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Uma vez que a competição obriga os jogadores a tomar decisões enquanto executam

ações intensas, a procura do rendimento ótimo exige cargas de treino específicas de

intensidade elevada, variadas e que se manifestem em curtos espaços de tempo

(Tenenbaum, LevyKolker, Sade, Liebermann, & Lidor, 1996). Num âmbito mais

específico do treino de força (TF), por exemplo, o treino deverá incluir tarefas que

impliquem tomadas de decisão características da modalidade (Fajardo, 1999) (ver figura

1.3).

Figura 1.3. Exemplo de um exercício que contempla a colaboração e oposição

característica dos desportos de equipa. Em função da atuação do defensor, o atacante

deve escolher entre o lançamento ou progressão com bola (Fajardo, 1999).

Na verdade, o próprio estímulo fisiológico poderá ser manipulado para que a resposta

motora não seja previamente idealizada e processada pelo executante. Assim, para além

da complexidade na tomada de decisão técnico-tática, também a tarefa de força

específica pode ser constrangida para replicar o estímulo fisiológico imprevisível que

caracteriza todas as ações de cooperação-oposição em jogo.

http://www.youtube.com/watch?v=M7aFrylaCvY&feature=youtu.be

http://www.youtube.com/watch?v=M7aFrylaCvY&feature=youtu.be

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Numa dimensão técnico-táctica deve-se privilegiar o jogo como elemento fundamental e

recorrer à sua problematização, o que poderá ser feito a partir da manipulação da sua

estrutura organizacional, ou seja, de variáveis como as dimensões do terreno de jogo, o

número de jogadores e as regras (Hill-Haas et al., 2011).

1.1.4. Dimensões dos jogos reduzidos

Algumas características dos JDC como a variabilidade e a imprevisibilidade têm sido

utilizadas com recurso a exercícios específicos que visam determinadas condicionantes

que integram as variáveis do jogo. Os JR são habitualmente praticados em áreas

reduzidas, envolvem um número reduzido de jogadores e utilizam regras modificadas

(Hill-Haas et al., 2011). Uma vez que este tipo de jogos permite a manipulação de

variáveis que podem influenciar a intensidade do exercício e replicar as exigências

competitivas, o aumento da produção científica centrada no estudo dos JR pode

contribuir para uma análise mais detalhada das principais dimensões do jogo: técnico-

tática, fisiológica e psicológica.

Relativamente à dimensão técnico-tática, os JR facilitam a assimilação de conceitos

técnicos, táticos individuais e táticos coletivos (Owen, 2003). Numa perspetiva de treino

no alto rendimento, é importante decompor o jogo através do uso de diferentes formatos

de JR com alteração do número de participantes (Rampinini, Impellizzeri, Castagna,

Abt, Chamari, Sassi, et al., 2007). De um modo geral, as formas de jogo mais reduzidas

permitem aos jogadores contactos mais frequentes com a bola em diferentes situações

de jogo, o que requer a utilização de habilidades técnico-táticas ajustadas ao contexto

(Capranica, Tessitore, Guidetti, & Figura, 2001).

Numa dimensão fisiológica, a prática dos JR pode ser usada como uma ferramenta para

a melhoria da condição física, uma vez que induz níveis de frequência cardíaca (FC)

próximos dos 90 a 95% da FC máxima (Hoff, Wisloff, Engen, Kemi, & Helgerud,

2002). Estas intensidades elevadas favorecem o desenvolvimento da performance

aeróbia (Helgerud, Engen, Wisloff, & Hoff, 2001), indo de encontro a valores já

verificados em algumas formas de treino intervalado (Impellizzeri, Marcora, Castagna,

Reilly, Sassi, Iaia, et al., 2006). Na verdade, os benefícios obtidos no treino são

máximos quando a intensidade utilizada é similar aquela que se verifica em competição

(Mallo & Navarro, 2008). Adicionalmente, a inclusão de JR nos programas de treino

Capítulo 1 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

31

promove respostas e intensidades neuromusculares específicas da modalidade, para

além de aumentar a motivação para realizar as tarefas (Hill-Haas et al., 2011).

Vários estudos sugerem que a resposta fisiológica é afetada pela alteração de algumas

condicionantes do jogo (Fanchini, Azzalin, Castagna, Schena, McCall, & Impellizzeri,

2011a; Kelly & Drust, 2009; Sampaio, García, Maçãs, Ibáñez, Abrantes, & Caixinha,

2007). A duração, tempos de descanso, o número de jogadores, dimensões do terreno,

alteração de regras e feedback por parte do técnico têm um impacto direto sobre os

fatores fisiológicos e psicofisiológicos, refletidos pelos valores de FC e perceção

subjetiva de esforço (PSE1) (Hill-Haas et al., 2011), respetivamente. A avaliação

sistemática destes parâmetros, em conjunto com as ações técnicas e táticas (ATT), pode

contribuir para a obtenção de resultados válidos e mais fiáveis, melhorando

significativamente o processo de treino (Tessitore, Meeusen, Piacentini, Demarie, &

Capranica, 2006). A investigação centrada na manipulação de variáveis e o seu efeito na

resposta fisiológica, psicológica e técnico-tática em JR é abundante no futebol, mas

praticamente omissa no Andebol. Apesar disso, a utilização de JR no Andebol parece

contribuir para o desenvolvimento da capacidade aeróbia em contexto de jogo,

preservando componentes específicos da modalidade como a agilidade, tempos de

reação e coordenação óculo-manual (Buchheit, Laursen, Kuhnle, Ruch, Renaud, &

Ahmaidi, 2009).

Apesar dos JR permitirem uma reprodução fiel do padrão cardiovascular e técnico-

tático necessário à preparação desportiva dos jogadores (Reilly & White, 2004), replicar

o padrão de solicitação muscular parece bem mais complexo. Para que as adaptações da

força sejam significativas, tanto a nível morfológico como neuromuscular, são

necessários programas de treino que respeitem metodologias específicas. Por exemplo,

para o aumento da massa muscular são necessárias intensidades próximas de 70 a 80%

de uma repetição máxima (Moore, Burgomaster, Schofield, Gibala, Sale, & Phillips,

2004), enquanto as adaptações neurais requerem intensidades entre 90 a 100% de uma

repetição máxima (Takarada, Takazawa, Sato, Takebayashi, Tanaka, & Ishii, 2000).

1 A PSE é um método de avaliação psico-fisiológico da intensidade percebida do esforço, desenvolvido no início dos anos 60 por Gunnar Borg. Este autor desenvolveu a escala da percepção subjectiva de esforço, considerada fiável e de fácil compreensão, que tem sido aplicada na monitorização do exercício em populações adultas (ver Borg, 1990 e 1998; Faulkner & Eston, 2008).

Capítulo 1 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

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1.1.4.1. Dimensão muscular

Ao contrário do que acontece com a aptidão cardiovascular e ATT, a força muscular

não é suficientemente solicitada através da prática dos JR. Esta ideia é suportada pela

relação entre a PSE e as concentrações de lactato sanguíneo já investigada (Aroso,

Rebelo, & Gomes Pereira, 2004). Neste estudo verificaram-se concentrações de lactato

de 4.9±2.0 e 2.6±1.7 (mmol/L) e valores de PSE de 14.5±1.7 e 13.3±0.9 em jogo 3x3 e

4x4, respetivamente (Aroso et al., 2004). Assim, diferentes formatos de JR induziram

valores elevados de PSE mas não de lactato sanguíneo, o que sugere uma perceção

elevada da intensidade do esforço que não foi correspondida por uma solicitação

muscular significativa. Como já foi referido, adaptações musculares significativas

exigem cargas específicas, só possíveis com recurso a unidades especiais de TF

(Zatsiorsky & Kraemer, 2006). Neste sentido, torna-se importante perceber os efeitos da

interação entre as unidades de TF e as unidades de treino de pavilhão, procurando obter

modelos de periodização que permitam a sua concorrência e produzam melhorias na

performance.

O TF é essencial para se atingir elevadas performances durante a competição. Na

verdade, os objetivos finais do TF passam por aumentar a força e/ou assegurar a sua

conservação nos diferentes períodos do ciclo anual de treino, atingir um

desenvolvimento harmonioso de todos os grupos musculares (Zatsiorsky & Kraemer,

2006) e alcançar elevados índices de força e potência nos movimentos que caracterizam

cada uma das modalidades (Verkhoshansky, 2006). Em suma, o potencial de força deve

ser manifestado com base no princípio da conjugação de ações, ou seja, melhoria da

capacidade física funcional e habilidades técnico-táticas (Verkhoshansky, 2006).

O Andebol é um jogo caracterizado por movimentos complexos com e sem bola,

executados em regimes variáveis de velocidade e força como acelerações repetidas,

sprints, saltos, mudanças de direção e contacto físico entre jogadores (Ronglan,

Raastad, & Borgesen, 2006). A necessidade que o jogador de Andebol tem de realizar

ações de curta duração a alta intensidade reforça o TF como uma ferramenta

indispensável à melhoria da sua performance, ajudando-o na execução de tarefas de

competição que implicam níveis elevados de força aliados a velocidades de execução

rápidas (Ziv & Lidor, 2009). Partindo destes pressupostos e considerando que

adaptações significativas de força exigem sessões de treino específicas, parece evidente

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33

que a concorrência entre as unidades de TF e as unidades de treino de pavilhão deve ser

cuidadosamente manipulada na periodização e planeamento do treino.

Já foi demonstrado que a adição de sessões específicas de TF máxima ao treino técnico-

tático de Andebol resulta em ganhos maximais de força e aumento da velocidade de

remate, embora possa comprometer ganhos de força explosiva nos membros inferiores e

resistência de corrida (Gorostiaga, Izquierdo, Iturralde, Ruesta, & Ibanez, 1999).

Aparentemente, o treino conjunto de força máxima e resistência pode inibir a médio

prazo capacidade de produzir força (Hickson, 1980), provavelmente pela dificuldade de

adaptação da estrutura muscular ao treino combinado (Zatsiorsky & Kraemer, 2006).

Figura 1.4. Mudanças na resposta da capacidade força em 3 tipos de treino. Os registos

dos grupos do treino de força e treino de força + resistência foram semanais. O grupo do

treino de resistência foi avaliado no início e final do protocolo (Hickson, 1980).

No entanto, já foram relatados ganhos em ambas as capacidades quando a força foi

treinada separadamente da resistência (Collins & Snow, 1993; Leveritt & Abernethy,

1999). Neste sentido, sugere-se que o treino concorrente de força e resistência pode

resultar em ganhos para ambas as capacidades, desde que os mecanismos de

recuperação sejam respeitados (Wong, Chaouachi, Chamari, Dellal, & Wisloff, 2010).

Apesar destes resultados, o conhecimento acerca da ordem com que se treina a força e

resistência é ainda escasso. Para além disso, a literatura é pobre no que diz respeito aos

efeitos imediatos que TF tem na performance técnico-tática dos jogadores.

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34

A magnitude e a fonte de fadiga no TF podem variar de acordo com o tipo de contração

muscular (Babault, Desbrosses, Fabre, Michaut, & Pousson, 2006), intensidade

(Linnamo, Newton, Hakkinen, Komi, Davie, McGuigan, et al., 2000), velocidade de

execução (Linnamo, Hakkinen, & Komi, 1998) e tempo de descanso (Pattersson,

Pearson, & Fisher, 1985). Neste sentido, importa perceber quais as adaptações agudas e

crónicas induzidas pelo TF, para que a seleção da localização das sessões nos

microciclos e mesociclos de treino seja criteriosa e salvaguarde uma metodologia

eficiente.

Em relação às adaptações crónicas, o treino de hipertrofia, caracterizado por

intensidades próximas das 10 repetições máximas (Kraemer, Marchitelli, Gordon,

Harman, Dziados, Mello, et al., 1990), promove alterações morfológicas como o

aumento da secção transversal do músculo (Moore et al., 2004) e facilita o aumento da

força muscular (Verkhoshansky, 2006). Contudo, a capacidade de gerar força depende

igualmente das adaptações do sistema nervoso. Assim, o treino de adaptações neurais

requer intensidades próximas dos 90% de uma repetição máxima, para que haja um

maior recrutamento de fibras musculares (Takarada et al., 2000) e melhor sincronização

entre as unidades motoras responsáveis pelo mecanismo de contração muscular

(Fajardo, 1999). Neste sentido, a combinação entre o aumento da massa muscular e o

trabalho de natureza neural é fundamental para que o desenvolvimento da capacidade

força seja significativo. Quando comparadas no tempo, as adaptações induzidas pelos

programas de hipertrofia são mais lentas e tardias do que as verificadas no treino neural

(Sale, 1988). Por esse motivo, as adaptações hipertróficas requerem um maior número

de unidades de treino. Apesar destas investigações sublinharem importantes adaptações

crónicas ao TF, os efeitos agudos que estes programas de treino induzem na

performance dos jogadores de Andebol são pouco explorados na literatura. Esta

escassez de informação dificulta a tarefa dos treinadores na organização semanal do

processo de treino que inclua sessões de TF combinadas com sessões de treino técnico-

tático. No entanto, existem estudos focados nos efeitos neuromusculares agudos do TF

máxima que podem ajudar a perceber algumas variações nos perfis de desempenho dos

jogadores imediatamente após uma sessão de TF (Babault et al., 2006; Bigland-Ritchie,

1981; McCaulley, McBride, Cormie, Hudson, Nuzzo, Quindry, et al., 2009; Moore et

al., 2004; Sale, 1992).

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35

Os períodos curtos de recuperação no treino de hipertrofia parecem aumentar o

recrutamento de unidades motoras, apesar do decréscimo da capacidade de gerar força

(Sale, 1992), consequência da fadiga de origem periférica (Moore et al., 2004).

Contrariamente ao treino hipertrófico, a fonte de fadiga observada nos protocolos

neurais parece estar associada a uma falha na ativação do sistema nervoso central

(McCaulley et al., 2009), resultando na diminuição da atividade muscular e deterioração

da produção de força (Bigland-Ritchie, 1981). Para além disso, o treino neural induz

concentrações de lactato significativamente inferiores aos protocolos de hipertrofia,

muito em parte devido aos intervalos de recuperação prolongados entre séries

(McCaulley et al., 2009). Imediatamente após a realização do TF, os protocolos neurais

parecem estimular grande parte das fibras tipo II (Sale, 1992), enquanto os protocolos

de hipertrofia resultam num decréscimo do peak force e capacidade de gerar força,

aumentando no entanto a atividade elétrica dos músculos (McCaulley et al., 2009). Este

fenómeno é conhecido por ineficiência neuromuscular (Deschenes, Judelson, Kraemer,

Meskaitis, Volek, Nindl, et al., 2000) e pode ser um forte sinal de fadiga periférica

(Babault et al., 2006). Para além destes indicadores, também já foi observado que os

processos de recuperação da capacidade de gerar força (24h e 48h) foram mais rápidos

após um protocolo de hipertrofia do que o verificado no neural (McCaulley et al., 2009).

Em suma, tanto os treinos neural como o hipertrófico resultam em fadiga

neuromuscular, provavelmente com origem em diferentes fontes, central e periférica

respetivamente. Quando comparados com outas metodologias de TF, os protocolos de

hipertrofia e adaptações neurais promovem efeitos imediatos na diminuição do

percentual do peak force isométrico e uma quebra na capacidade de gerar força,

enquanto, por exemplo, os treinos de resistência e potência não são capazes de induzir

alterações significativas (McCaulley et al., 2009).

Apesar destas informações poderem e deverem ser consideradas na prescrição de um

plano de treino, já foi sublinhada a escassez de investigação científica focada nos efeitos

agudos do TF nas ações desportivas do jogador de Andebol. O lapso que a literatura

apresenta neste domínio faz com que os técnicos de Andebol não possuam informação

suficiente e válida que lhes permita identificar os momentos mais adequados para a

inclusão do TF no microciclo e/ou unidades de treino.

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36

1.1.4.2. Dimensão energética

São várias as investigações que se têm focado nas respostas fisiológicas agudas a JR e

formas intervaladas de treino (Balsom, Gaitanos, Soderlund, & Ekblom, 1999; Dellal,

Chamari, Pintus, Girard, Cotte, & Keller, 2008; Sassi, Reilly, & Impellizzeri, 2004).

Considerando durações de exercício idênticas, as conclusões desses estudos apontam

para a existência de intensidades semelhantes em ambos os formatos. Para além disso,

já se verificaram adaptações semelhantes ao nível da capacidade aeróbia e realização de

exercícios intermitentes com mudanças de direção após um programa de treino de 6

semanas que contemplou JR e regimes de treino intervalado (Reilly & White, 2004). No

entanto, a variabilidade dos estímulos parece ser superior nos JR em comparação com

os exercícios intervalados (ver figura 1.5), provavelmente pela natureza específica das

ações inerentes ao jogo (Hill-Haas et al., 2011).

Figura 1.5. Valores médios (%FC máxima) da intensidade do exercício em diferentes

situações de treino de futebol (Hill-Haas et al., 2011).

Aparentemente, tanto os JR como os regimes de treino intervalado são ferramentas úteis

para o desenvolvimento da performance aeróbia ao longo da época desportiva. Na

verdade, já foi observado que ambos os métodos induziram valores idênticos da

%FCmax e PSE após 12 semanas de treino (Impellizzeri et al., 2006).

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37

A intensidade do esforço em JR tem sido avaliada sobretudo com recurso à análise da

FC, lactato sanguíneo e PSE (Hill-Haas et al., 2011). Contudo, a FC parece ser a

ferramenta mais privilegiada, sendo considerada um método válido e fiável na avaliação

da intensidade do esforço em vários desportos (Achten & Jeukendrup, 2003). Por

exemplo, já foi mostrado que a resposta fisiológica é influenciada pela alteração de

fatores como a duração do jogo (Duarte, Batalha, Folgado, & Sampaio, 2009), área do

campo (Kelly & Drust, 2009), regras do jogo (Hill-Haas, Coutts, Dawson, & Rowsell,

2010) e número de jogadores (Owen, Twist, & Ford, 2004; Sampaio et al., 2007). Mais,

a relação entre a média dos valores da FC e do consumo de oxigénio (VO2) detetada em

testes laboratoriais é semelhante à relação da FC com o VO2 verificada durante a

avaliação do esforço em JR (Esposito, Impellizzeri, Margonato, Vanni, Pizzini, &

Veicsteinas, 2004).

Apesar da validade desta variável, o tempo exigido para análise e interpretação dos

dados pode representar um constrangimento para os treinadores. Também o lactato

sanguíneo tem sido utilizado com frequência na avaliação da intensidade esforço, no

entanto é considerado um indicador pobre das concentrações de lactato muscular em

atividades de carácter intermitente (Krustrup, Mohr, Steensberg, Bencke, Kjaer, &

Bangsbo, 2006). Deste modo, a PSE apresenta-se como um método simples, não

invasivo e sem custos para a monitorização da intensidade do exercício (Borg, 1982). O

uso da PSE surge assim como uma alternativa válida para quantificar a intensidade do

esforço durante uma sessão de treino (Impellizzeri, Rampinini, Coutts, Sassi, &

Marcora, 2004a).

A PSE pode ser definida como a intensidade subjetiva de esforço, desconforto e/ou

fadiga sentida durante a realização de um exercício físico (Robertson, 2001). A

interpretação fisiológica dos aspetos cardiorrespiratórios, metabólicos e musculares tem

um papel importante na regulação da intensidade do exercício. No entanto, a atividade

desportiva não possui apenas uma componente física. A PSE tem uma natureza

multifatorial que não é mediada apenas por fatores fisiológicos mas também por fatores

psicológicos (Borg, 1982). Neste sentido, a PSE é considerada um indicador

psicofisiológico para a obtenção do grau do esforço físico, integrando informações

como sinais deduzidos do trabalho muscular, cardiopulmonar e do sistema nervoso

central (Robertson, 2000). Para além disso, tem-se mostrado um método simples e

válido na quantificação da intensidade de sessões de treino, quer em esforços de carácter

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38

contínuo (Foster, Florhaug, Franklin, Gottschall, Hrovatin, Parker, et al., 2001) como

em esforços intermitentes (Impellizzeri et al., 2004a). A avaliação da PSE foi já

sugerida como um método mais apropriado na avaliação da intensidade do esforço do

que a análise individualizada das variáveis fisiológicas (Borg, 1982). No entanto, é

necessário integrar as informações obtidas a partir dos três diferentes tipos de variáveis

de esforço - performance/rendimento, avaliações fisiológicas e respostas de perceção -

para que os resultados obtidos sejam mais fiáveis.

Aparentemente existe uma relação forte entre as estimativas do esforço percebido e as

concentrações de lactato, o que sugere que o aumento da PSE pode estar relacionado

com o aumento da FC e lactato sanguíneo (Borg, Hassmen, & Lagerstrom, 1987). Na

verdade, já foi demonstrado que a combinação dos dados obtidos pela avaliação da FC e

concentração de lactato no sangue com a PSE apresentou resultados mais fiáveis do que

a análise isolada da FC ou concentração de lactato (Chen, Fan, & Moe, 2002). Em

suma, a PSE está correlacionada com muitas formas de avaliação da intensidade do

exercício, como o consumo de oxigénio, ventilação, frequência respiratória,

concentração de lactato no sangue e FC (Faulkner & Eston, 2008). Em conjunto, todos

estes fatores parecem suportar a PSE como um método fiável na avaliação da

intensidade em esforços intermitentes, os de manifestação mais frequente nos JDC. No

entanto, não existe nenhuma evidência que permita afirmar que um método de avaliação

é mais fiável do que outro, pelo que a monitorização da intensidade nos JR deve ser

feita através da combinação de métodos (Coutts, Rampinini, Marcora, Castagna, &

Impellizzeri, 2009).

Compreender os efeitos que os vários fatores externos têm na intensidade do esforço e

performance técnico-tática pode permitir uma melhor integração dos JR no processo de

treino (Fanchini, Azzalin, Castagna, Schena, Mccall, & Impellizzeri, 2011b). Neste

contexto, a análise do comportamento dos jogadores e das equipas torna-se

preponderante na avaliação, organização e prescrição do treino.

1.1.4.3. Dimensão técnico-tática

O carácter complexo e multidimensional dos JDC apresenta constrangimentos na

análise do rendimento desportivo, sobretudo porque o seu produto final é influenciado

por fatores físicos, psíquicos e técnico-táticos (Glazier, 2010). Segundo a teoria das

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39

performances interativas, a performance de uma equipa é afetada pela qualidade e tipo

de oposição, para além de diferentes jogadores serem influenciados pelo mesmo tipo de

oposição de forma distinta (O'Donoghue, 2009). Deste modo, a relação das equipas com

os jogadores adversários torna-se um fator chave na interpretação dos comportamentos

durante o jogo (McGarry, 2009). Todas estas interações fazem com que a performance

desportiva não possa ser avaliada com recurso a dados isolados, sendo necessária uma

abordagem combinada (ver figura 1.6) que considere a complexidade dos sistemas

(Hughes & Franks, 2004).

Figura 1.6. Abordagem a sistemas complexos utilizada para análise da performance

desportiva (Hughes & Franks, 2004).

Apesar das estatísticas do jogo captarem detalhadamente o que se passa em jogo

(Sampaio, Ibanez, Feu, Lorenzo, Gomez, & Ortega, 2008), a investigação científica

atual acrescenta a necessidade de criar modelos multidimensionais para o estudo de

sistemas complexos. A análise da performance deve considerar fatores como o processo

e o resultado (ver figura 1.7), ou seja, a descrição das condutas dos jogadores e sua

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40

eficácia no tempo, bem como o resultado final da interação entre as equipas (Grehaigne

& Godbout, 1995). Por exemplo, o enquadramento temporal das ações registadas pode

contemplar o equilíbrio do resultado e as condutas do adversário, para que a perspetiva

global do jogo se rega pelo princípio de que os elementos não têm significado, senão na

sua relação com o conjunto (Volossovitch, 2008). Deste modo, a análise do jogo deve

respeitar uma abordagem dinâmica que interprete a sua realidade complexa (Bar-Yam,

2003).

Figura 1.7. Duas dimensões da análise do jogo (Volossovitch, 2008).

No Andebol, a performance tem sido avaliada com recurso a indicadores como remates

concretizados e falhados da zona dos 9m, da zona dos 6m (pivot e extremos) e em

contra-ataque, assistências, livres de 7 metros conquistados, falhas técnicas no ataque e

diferença entre golos marcados e sofridos (Gruić, Vuleta, & Milanović, 2006; Ohnjec,

Vuleta, Milanovic, & Gruic, 2008). Outros indicadores como a eficácia dos guarda-

redes, ações defensivas e eficácia do remate em ataque organizado (Magalhães, 1999)

também já foram utilizados com o objetivo de definir indicadores que associassem a

performance à classificação final de provas oficiais da modalidade.

Em conjunto com as habilidades técnico-táticas, a performance do remate também tem

sido referida como um parâmetro chave para o sucesso no Andebol (Hoff &

Almasbalck, 1995). Nesse sentido, a precisão do gesto técnico e a velocidade da bola

são consideradas variáveis decisivas para o sucesso do remate (Fleck, Smith, Craib,

Denahan, Snow, & Mitchell, 1992). O resultado da combinação entre a precisão e

velocidade do gesto define a eficácia do remate, que é determinada sobretudo por

fatores coordenativos, mecânicos e pela força dos membros superiores e inferiores

(Fleck et al., 1992; Gorostiaga, Granados, Ibanez, & Izquierdo, 2005).

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41

Torna-se evidente que a diversidade de ações que caracteriza o Andebol requer

preparação específica da força (Boraczynski & Urniaz, 2008), uma vez que o treino

desta capacidade tem um impacto significativo na execução de ações fundamentais no

jogo como o sprint e impulsão vertical máxima (Ronglan et al., 2006). O TF com

intensidades elevadas responde à necessidade de produzir níveis elevados de força em

curtos espaços de tempo (Zatsiorsky & Kraemer, 2006) e à máxima velocidade de

execução (Harris, Stone, O’Bryant, Proulx, & Johnson, 2000), indo de encontro aos

requisitos do jogo de andebol (Rannou, Prioux, Zouhal, Gratas-Delamarche, &

Delamarche, 2001). No entanto, uma vez que a execução técnica é uma peça chave para

a otimização dos resultados desportivos, o TF deve englobar exercícios que reflitam o

conjunto de ações motoras, gestos técnicos e grupos musculares mais solicitados na

modalidade (Marques & Gonzalez-Badillo, 2006). Para além disso, o TF deve respeitar

velocidades, acelerações e amplitudes gestuais idênticas às dos gestos competitivos

específicos (Verkhoshansky, 2006).

Em síntese, a performance desportiva é influenciada pelas capacidades técnicas, táticas

e físicas, cabendo aos técnicos a sua inclusão e organização no processo de treino (Jones

& Drust, 2007). Neste âmbito, os JR são reconhecidos como uma estratégia eficiente

para aumentar o tempo de prática efetiva dos jogadores, solicitando em simultâneo as

habilidades técnicas, táticas e capacidades físicas (Rampinini, Impellizzeri, et al., 2007).

Ao contrário do que acontece nos exercícios de corrida, a presença de bola nos JR

parece facilitar o desenvolvimento das habilidades técnico-táticas em contexto de jogo,

uma vez que permite a replicação de movimentos específicos, intensidades e requisitos

técnicos da competição (Gamble, 2004; Little, 2009). As situações de JR aumentam a

frequência e exigência das ATT (Jones & Drust, 2007), verificando-se um aumento do

número de ações nos formatos de jogo com menor número de jogadores (Hill-Haas et

al., 2011). No caso particular do Andebol, os formatos de jogo reduzido parecem

aumentar a frequência individual de passes, receções, remates, desmarcações e

interceções em idades jovens (Ribeiro & Volossovitch, 2004).

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42

Figura 1.8. Média ± SD de contactos com a bola em jogo 4x4 e 8x8 de futebol (Jones &

Drust, 2007).

* Diferenças estatisticamente significativas.

No entanto, a frequência das ATT não pode considerada de forma isolada na avaliação

da performance de uma equipa, uma vez que o principal objetivo dos JDC deve estar

direcionado para as ações funcionais, ou seja, para a eficácia das ações (Araujo et al.,

2006). No futebol, a comparação de formatos de JR 4x4 e 6x6 mostrou que apesar de ter

sido previsível observar um maior número de ATT no jogo 4x4, a alteração do número

de jogadores não influenciou significativamente a eficácia das ações (Abrantes, Nunes,

Macas, Leite, & Sampaio, 2012). Estes resultados sugerem a realização de investigações

futuras que esclareçam a relação entre a manipulação de constrangimentos da tarefa e a

eficácia das ações. Para isso, é importante não descurar que os modelos de eficácia são

diferentes em cada equipa e em cada jogo, influenciados em parte pelo tipo de oposição,

interação entre jogadores e sistemas utilizados nos processos defensivo e ofensivo

(Vuleta, Milanović, Gruić, & Ohnjec, 2005). Só assim é que o jogo poderá ser analisado

através de uma abordagem dinâmica que considere o processo e contexto em que os

jogadores estão envolvidos.

A importância demonstrada que o TF e a os JR têm no processo de treino de Andebol

acentua a necessidade de investigar os efeitos que a inclusão de ambos tem na

performance dos jogadores. Em particular, o TF com cargas elevadas está associado ao

declínio da força muscular e a manifestações de fadiga agudas (McCaulley et al., 2009),

provocando, por exemplo, a diminuição da eficácia do passe em jogadores de

basquetebol na realização de exercícios analíticos (Lyons, Al-Nakeeb, & Nevill, 2006).

No entanto, a análise isolada de um exercício ou gesto técnico é insuficiente, uma vez

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43

que desconsidera a complexidade e o carácter multidimensional do jogo. Deste modo,

continuam a ser escassos os dados acerca dos efeitos agudos do TF máxima na

performance técnico-tática em contexto de jogo, em particular no Andebol.

1.1.5. Planeamento a curto prazo nos jogos desportivos coletivos

1.1.5.1. Efeitos agudos do treino de força nos perfis de performance de

andebolistas

O Andebol é uma modalidade dinâmica que requer jogadores velozes, ágeis, resistentes,

coordenados e fortes (Hatzimanouil & Oxizoglou, 2004). No caso particular da força

muscular, ela é responsável por assegurar o desenvolvimento das propriedades

funcionais específicas da modalidade e por promover uma estrutura dinâmica perfeita

das ações motoras (Fleck & Kraemer, 2004). Para além disso, a força muscular é um

pressuposto fundamental para o desenvolvimento da potência, um dos principais

requisitos do rendimento desportivo (Allerheiligen, 1994). Assim, o aumento do

potencial motor impõe exercícios de competição, incluindo os de força, combinados

com velocidades de execução elevadas (Verkhoshansky, 2006). O aumento na produção

de potência é conseguido sobretudo pelo desenvolvimento da capacidade motora, que

por sua vez depende do aumento da capacidade dos sistemas do corpo produzirem

energia e da perfeição dos skills dos jogadores para aplicarem todo o seu potencial

motor em competição (ver figura 1.9).

Figura 1.9. Os principais fatores responsáveis por determinar o resultado desportivo

(Verkhoshansky, 2006).

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44

Vários estudos demonstram que programas periodizados de TF são determinantes no

desenvolvimento de ações motoras como a impulsão vertical (Christou, Smilios,

Sotiropoulos, Volaklis, Pilianidis, & Tokmakidis, 2006; Gorostiaga, Izquierdo, Ruesta,

Iribarren, Gonzalez-Badillo, & Ibanez, 2004; Luebbers, Potteiger, Hulver, Thyfault,

Carper, & Lockwood, 2003), agilidade e velocidade de deslocamento (Christou et al.,

2006; McBride, Triplett-McBride, Davie, & Newton, 2002; Miller, Herniman, Ricard,

Cheatham, & Michael, 2006). No Andebol, já foi verificado que o TF é preponderante

para o aumento da velocidade de remate (Gorostiaga et al., 1999), o que em conjunto

com a melhoria das ações acima referidas pressupõe que o desenvolvimento desta

capacidade acrescenta a possibilidade de recurso a mais estratégias e táticas por parte

dos jogadores. Deste modo, sem negar a importância de outras capacidades físicas, o

planeamento do TF assume uma elevada preponderância no progresso desportivo,

devendo seguir uma direção lógica para maximizar a performance desportiva

(Verkhoshansky, 2006).

A importância que cada microciclo de força assume na periodização e planificação do

treino varia, principalmente em função de fatores como a frequência do TF, objetivos do

TF, intensidade do TF e variabilidade dos exercícios (Badillo, 2000). Com vista à

obtenção do máximo rendimento, a distribuição e a carga dos exercícios devem ser

parâmetros considerados aquando da prescrição de um programa de TF (Zatsiorsky &

Kraemer, 2006). No entanto, outros constrangimentos se emergem, como a localização

da unidade de TF no microciclo e o tempo de recuperação entre sessões.

Ao contrário do que acontece em modalidades como o halterofilismo e culturismo, no

Andebol não se pode considerar a força como única componente do treino, uma vez que

a necessidade de desenvolver capacidades como a resistência, velocidade e habilidades

técnicas, faz com que o TF se assuma como parte do processo de treino. Assim, é

preciso ter em atenção as dificuldades que o organismo pode ter em se adaptar quando

as solicitações são múltiplas e em simultâneo, correndo-se o risco de obter modificações

insignificantes nas diferentes capacidades motoras (Zatsiorsky & Kraemer, 2006). Neste

sentido, os efeitos da fadiga devem ser interpretados e manipulados de forma cautelosa

durante o planeamento de curta duração(Hansen, Kvorning, Kjaer, & Sjøgaard, 2001).

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45

De acordo com o modelo “ dois fatores” (Zatsiorsky & Kraemer, 2006), o efeito agudo

do TF resulta da combinação de dois aspetos: ganhos na aptidão física (mudanças lentas

na componente motora da performance desportiva) e fadiga (diminuição transitória e

reversível da capacidade de trabalho). Após uma unidade de TF, o potencial de

performance desportiva de um atleta melhora devido aos ganhos de aptidão física mas

deteriora-se devido à fadiga. Assim, o resultado final é o somatório das mudanças

positivas e negativas ocorridas neste processo (ver figura 1.10).

Figura 1.10. Modelo de treino “dois fatores”. O efeito imediato de uma sessão de TF é

caracterizado pelo somatório de dois processos: ganhos na aptidão física e fadiga

(Zatsiorsky & Kraemer, 2006).

Desta forma, os ganhos de aptidão física resultantes de uma sessão de treino de força

são moderados em magnitude mas prolongam-se no tempo, enquanto o efeito da fadiga

é superior em magnitude mas relativamente curto em duração. Este é mais um fator a ter

em conta no estabelecimento de etapas de TF, exigindo aos técnicos conhecimentos

profundos acerca da periodização e planeamento desportivo (Gamble, 2010).

A periodização tradicional, caracterizada pela divisão do programa desportivo anual em

pequenos períodos e unidades de treino, tem sido limitada por uma série de fatores. De

entre eles destacam-se o conflito das respostas fisiológicas produzido pelo treino

dirigido a várias capacidades motoras em simultâneo, a fadiga excessiva provocada por

longos períodos com múltiplos objetivos de treino, o fraco estímulo induzido por cargas

leves/médias e a incapacidade de proporcionar picos de forma ao longo da época

(Issurin, 2008). Como consequência, um planeamento baseado no método tradicional

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46

pode resultar em perdas acentuadas na massa magra (Allerheiligen, 1994), força

máxima (Astorino, Tam, Rietschel, Johnson, & Freedman, 2004), potência máxima

anaeróbia (Lorenz, Reiman, & Walker, 2010) e até velocidade máxima (Fleck &

Kraemer, 2004). Desde logo, a aplicação de um método unidirecional não dá resposta às

múltiplas manifestações físicas e técnicas que a performance desportiva na maior parte

das modalidades requer (Zatsiorsky & Kraemer, 2006). Num período preparatório, por

exemplo, a necessidade de desenvolver a capacidade aeróbia e força muscular oferece

limitações à partida, já que são requeridas adaptações específicas a nível fisiológico e

morfológico que podem não ser compatíveis se trabalhadas em simultâneo (Issurin,

2008). Já no período competitivo, a periodização tradicional caracteriza-se pelo

estabelecimento de dois ou três macrociclos (Platonov, 1997). Mais uma vez, este tipo

de organização não satisfaz as exigências dos calendários congestionados que

caracterizam o grosso dos desportos coletivos de alto rendimento (Lago-Penas, Rey,

Lago-Ballesteros, Casais, & Dominguez, 2011).

Durante o período competitivo, os objetivos estão mais relacionados com os aspetos

técnico-táticos do que com o TF (Baker, 2007). Por esse motivo, o principal desafio dos

técnicos passa por manter os elevados níveis de potência muscular adquiridos durante

período preparatório (Porta, Viñaspre, & Morera, 1996). No entanto, a tarefa de

constituir programas de treino que mantenham ou elevem os níveis de força durante a

etapa competitiva é complexa (Wathen, Baechle, & Earle, 2000). Com o objetivo de

ultrapassar estas limitações, o modelo de periodização por blocos propõe quatro

princípios fundamentais de organização: concentração elevada de cargas de trabalho,

um número mínimo de capacidades alvo num só bloco, desenvolvimento consecutivo de

várias habilidades e estabelecimento de mesociclos especializados (Issurin, 2008). Ao

contrário do modelo tradicional no qual várias habilidades são desenvolvidas em

simultâneo, a organização por blocos pressupõe um desenvolvimento consecutivo de

habilidades especificamente selecionadas, compilando um plano anual que deve ser

entendido como uma sequência de estádios autónomos, onde os objetivos são obtidos

através de programas de treino parcialmente renovados(Issurin, 2008).

Tal como já foi referido, a tentativa de obter o máximo proveito do TF obriga a uma

periodização cuidada que exige a consideração de aspetos como a relação entre volume

e intensidade, ordem e sequência dos exercícios (Fleck & Kraemer, 2004). Por exemplo,

se um atleta realizar um exercício para membros inferiores (e.g. agachamento) e um

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47

exercício para membros superiores (e.g. supino), o número total de repetições será

superior se a sequência for vertical e inferior quando for horizontal (Zatsiorsky &

Kraemer, 2006), uma vez que solicitar de forma alternada os segmentos permite uma

recuperação mais eficaz (Bompa, 1993).

Apesar destas orientações, a literatura focada na periodização do TF nem sempre tem

em consideração as especificidades dos vários grupos musculares, como as diferenças

em número e tamanho das fibras, conteúdo de glicogénio e ATP, braços de alavanca e

força de contração. Para além de aspetos neurais como a coordenação intramuscular e

intermuscular, os fatores que mais influenciam a capacidade de um músculo gerar força

são o número de fibras musculares e respetiva área de secção transversal (Zatsiorsky &

Kraemer, 2006). Neste sentido, as diferenças de força podem ser justificadas pelo facto

de músculos com maior área de secção transversal terem um maior número de pontes

cruzadas (Orellana & Prada, 2000). De facto, já foi observado que para a mesma

intensidade de carga, jogadores profissionais de futebol foram capazes de executar o

exercício squat com cargas superiores às verificadas no exercício supino (Wisloff,

Helgerud, & Hoff, 1998). Numa outra investigação, verificou-se que após a aplicação de

um programa de TF de 12 semanas, os membros superiores obtiveram ganhos de 15%

relativamente aos obtidos nos membros inferiores (Sousa, Mendes, Abrantes, &

Sampaio, 2011). Apesar de este estudo ter sido realizado com sujeitos idosos, os

resultados sugerem que a menor funcionalidade quotidiana dos membros superiores

permite adaptações mais significativas quando sujeitos a um programa de TF (Enoka,

1988).

As conclusões observadas nestes estudos sugerem que quando sujeitos a intensidades

idênticas, os músculos dos membros inferiores são capazes de suportar cargas mais

elevadas do que os membros superiores. No entanto, a literatura ainda não fundamenta

de forma esclarecedora as diferenças que possam existir na adaptação aguda ao esforço

entre diferentes tipos de TF, dirigidos a membros superiores, inferiores ou a ambos.

Para além disso, não se conhece o modo como estas adaptações se podem refletir na

performance dos jogadores, traduzida pela eficácia das várias ações motoras, técnicas e

táticas. Mais, partindo do pressuposto já fundamentado que os JR devem fazer parte do

processo de treino, também se desconhecem os efeitos da relação e coabitação entre

diferentes tipos de TF e diferentes formatos de JR.

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48

A intensidade do esforço em JR pode ser analisada através dos movimentos dos

jogadores e/ou respostas fisiológicas/percetuais (Hill-Haas et al., 2011), cabendo ao

treinador selecionar e manipular os constrangimentos que podem influenciar essa

intensidade. De todas as variáveis já investigadas, interessa perceber de que forma é que

a redução do número de jogadores se pode refletir nas ATT, solicitação muscular e

energética. Tal como já foi referido, a utilização de JR permite a replicação de

intensidades de esforço e requisitos técnico-táticos próximos dos perfis de competição

(Little, 2009). A literatura também já mostrou que a redução do número de jogadores

aumenta os valores da FC (ver figura 1.11), lactato sanguíneo e resposta percetual

(Owen et al., 2004).

Figura 1.11. Intensidade do exercício (% FCmax) em vários formatos de jogos

reduzidos de futebol (Hill-Haas, Dawson, Coutts, & Rowsell, 2009).

Apesar de vários estudos se terem centrado na análise das ATT em JR (Capranica et al.,

2001; Duarte et al., 2009; Fanchini et al., 2011b; Jones & Drust, 2007; Kelly & Drust,

2009; Owen et al., 2004), os resultados não têm sido coerentes. Esta incerteza dificulta

o esclarecimento dos técnicos no que diz respeito à relação entre a intensidade do

exercício e o seu reflexo na performance técnico-tática. No entanto, sabe-se que a

prática dos JR induz intensidades de esforço elevadas, requerendo aos jogadores

tomadas de decisão rápidas e sobre o efeito da fadiga (Gabbett & Mulvey, 2008).

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49

Dado que fadiga atua nos sistemas nervosos central e periférico, a quebra no controlo

das ações por parte dos jogadores pode estar relacionada com uma má condição física,

em particular com a diminuição da força muscular (Lyons et al., 2006). Partindo do

princípio de que a maioria das atividades motoras que envolvem manifestações de força

e velocidade exigem um elevado estado de excitação para um ótimo desempenho

(Oxendine, 1984), a influência da fadiga sobre estas capacidades pode comprometer a

obtenção do rendimento pretendido (Knicker, Renshaw, Oldham, & Cairns, 2011).

Assim, é indispensável que os treinadores incluam programas específicos de TF no

processo de treino. Na verdade, o TF de alta intensidade contribui para melhoria da

performance desportiva, melhora a eficiência mecânica, diminui os gastos energéticos

(Heggelund, Fimland, Helgerud, & Hoff, 2013), aumenta o limiar anaeróbio (Marcinik,

Potts, Schlabach, Will, Dawson, & Hurley, 1991), reduz a FC de repouso (Antoniazzi,

Portela, & Dias, 1994) e reduz o risco de lesão (Fleck & Falkel, 1986).

A otimização dos processos de treino no Andebol deve considerar a complexidade e a

imprevisibilidade dos seus acontecimentos. A utilização de JR permite a replicação do

perfil fisiológico e padrões técnicos e táticos, preservando a variabilidade das ações em

contexto de jogo. No entanto, estas tarefas ficam aquém das solicitações musculares

requeridas em certos momentos da época desportiva, obrigando os treinadores a recorrer

a sessões específicas de TF. Em suma, a inclusão do TF e JR nos programas de treino

parece ser decisiva para a melhoria da performance dos jogadores, no entanto não se

conhecem os efeitos que a sua coabitação poderá ter no planeamento a curto prazo. A

resposta a esta questão irá esclarecer de forma mais sustentada a influência de sessões

específicas de TF na resposta fisiológica, técnica e tática dos jogadores em JR. Desta

forma, será aportado conhecimento aos treinadores que lhes permitirá otimizar o

processo de treino.

1.1.5.2. Variabilidade nos perfis de resposta de jovens futebolistas às cargas de

treino

O futebol de elite exige a utilização de processos de treino capazes de dar resposta à

complexidade do jogo e que reproduzam fielmente os seus padrões fisiológicos,

técnicos e táticos. Para que os treinadores possam prescrever cargas de treino que

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50

repliquem as exigências competitivas, é necessário identificar os indicadores de

performance que melhor definam o perfil de atividade dos jogadores em competição.

O futebol pode ser descrito como uma modalidade de caráter intermitente com uma

elevada variabilidade de estímulos e intensidades (Rebelo, Brito, Seabra, Oliveira, &

Krustrup, 2012) resultantes da luta pela posse de bola, sprints com mudanças de direção

e tomadas de decisão técnico-táticas (Gonçalves et al., 2013). Os valores de FC máxima

de um jogador durante um jogo de futebol raramente estão abaixo dos 65% (Bangsbo,

Mohr, & Krustrup, 2006), com valores médios e máximos de 85% e 98%,

respetivamente (Krustrup, Mohr, Ellingsgaard, & Bangsbo, 2005). Na verdade, os

jogadores são obrigados a executar ações de alta intensidade que incluem mudanças de

direção com períodos curtos de recuperação (Dellal, Keller, Carling, Chaouachi, Wong,

& Chamari, 2010). Neste sentido, a capacidade de recuperar e produzir ações

subsequentes de alta intensidade é considerada um requisito importante para se atingir

performances de alto nível (Girard, Mendez-Villanueva, & Bishop, 2011).

São vários os parâmetros que devem ser considerados na avaliação dos perfis físicos e

fisiológicos, tais como a FC (Buchheit, Simpson, Al Haddad, Bourdon, & Mendez-

Villanueva, 2012), perceção subjetiva do esforço (Impellizzeri, Rampinini, Coutts,

Sassi, & Marcora, 2004b), capacidade de executar sprints repetidos e mudanças de

direção (P., Chan, & Smith, 2012). Para além destas variáveis, os perfis de tempo-

movimento têm sido analisados com recurso a sistemas de posicionamento global (GPS)

(Casamichana & Castellano, 2010), considerados válidos para a avaliação da

performance em jogos desportivos coletivos (Coutts & Duffield, 2010). O uso extensivo

desta tecnologia deve-se em parte, ao facto dos aparelhos serem leves, pequenos,

portáteis e permitirem analisar vários jogadores em simultâneo (Aughey & Falloon,

2010). Partindo dos registos de posicionamento, estes instrumentos são capazes de

fornecer dados em tempo real relativos a velocidades de deslocamento, distâncias

percorridas e acelerações, normalmente descritos em função do posto específico

(Bradley, Di Mascio, Peart, Olsen, & Sheldon, 2010), nível de jogo (Mohr, Krustrup, &

Bangsbo, 2003) e idades (Buchheit, Mendez-Villanueva, Simpson, & Bourdon, 2010a).

Por exemplo, a distância total percorrida por jogadores jovens durante um jogo pode

variar entre 4435 e 8098m, sendo que 12% inclui ações de alta intensidade (Rebelo et

al., 2012), valores que tendem a aumentar com a idade (Buchheit et al., 2010a). Os

defesas percorrem menores distâncias em alta intensidade do que os outros jogadores,

Capítulo 1 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

51

enquanto os médios e laterais percorrem distancias semelhantes a alta intensidade

(Mohr et al., 2003). Curiosamente, a distância total percorrida durante um jogo está

fortemente correlacionada com a capacidade de realizar sprints repetidos (Rampinini,

Bishop, Marcora, Bravo, Sassi, & Impellizzeri, 2007). Neste sentido, a capacidade de

sprints repetidos é considerada uma qualidade chave na discriminação de jogadores

hábeis tecnicamente (Gabbett, 2010). Mais, as sequências de sprints repetidos e o

número de sprints são afetados pela idade, posto específico e tempo de jogo, sendo que

tendem a diminuir à medida que o jogo avança (Buchheit, Mendez-Villanueva,

Simpson, & Bourdon, 2010b).

As sessões de treino de futebol centram-se em situações jogadas com grande

variabilidade ao nível dos estímulos técnicos, táticos e fisiológicos (Hill-Haas et al.,

2011). Por essa razão, a manipulação de constrangimentos é uma tarefa complexa, uma

vez que as características individuais de cada jogador podem permitir a manifestação de

diferentes comportamentos em resposta a estímulos semelhantes (Chow, Davids,

Hristovski, Araujo, & Passos, 2011).

Muitas competições de equipas jovens organizam-se por escalões etários, no entanto é

importante considerar que a maioria das habilidades motoras experiencia

desenvolvimentos significativos durante o período pubertário (Cady, 1984; Côté &

Fraser-Thomas, 2007; Fernandez-Gonzalo, De Souza-Teixeira, Bresciani, Garcia-

Lopez, Hernandez-Murua, Jimenez-Jimenez, et al., 2010). Como consequência, os

perfis físicos e fisiológicos podem variar entre jogadores de idades e tempos de prática

semelhante (Cobley, Baker, Wattie, & McKenna, 2009). Ainda assim, os dados da

performance no treino poderão ser usados para classificar os jogadores e estabelecer

grupos homogéneos para a identificação de talentos e prescrição dos exercícios. Se os

jogadores forem agrupados em função de perfis físicos e fisiológicos semelhantes, a

variabilidade da resposta a nível fisiológico será minimizada, permitindo aos treinadores

ter um controlo mais fiável e eficiente sobre a resposta dos jogadores.

As cargas de treino semanais variam de acordo com as fases do ciclo anual, o que pode

induzir diferentes stresses fisiológicos nos jogadores (Impellizzeri et al., 2004a). O

período pré-competitivo é geralmente associado a maiores intensidades, principalmente

devido à elevada concentração de cargas de treino (Issurin, 2008) e tempo de treino

técnico-tático específico que, regra geral, consistem em JR de alta intensidade e jogos

simulados (Jeong, Reilly, Morton, Bae, & Drust, 2011). Por outro lado, o calendário do

Capítulo 1 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

52

período competitivo cria constrangimentos como a recuperação após o jogo e

preparação para o jogo seguinte (Gastin, Fahrner, Cook, Huntsman, Meyer, &

Robinson, 2010). Assim, a principal preocupação dos treinadores durante este período é

manter a capacidade física que os jogadores adquiriram durante o pré-competitivo

(Reilly, 2007). Nesta linha de raciocínio, um estudo com jogadores jovens de elite

mostrou que, no geral, a carga fisiológica da semana de treino foi superior no período

pré-competitivo em comparação com o competitivo, verificando-se valores mais

elevados de FC, mais tempo passado em zonas elevadas de FC e valores elevados de

PSE (Jeong et al., 2011).

Aparentemente, as cargas de treino semanais variam de acordo com a idade,

observando-se um aumento da intensidade em idades mais avançadas, provavelmente

pelo enfoque no desenvolvimento das capacidades físicas e preparação para a

competição (Wrigley, Drust, Stratton, Scott, & Gregson, 2012). Como resultado, os

microciclos são ajustados e adequados a esses objetivos. Por exemplo, a literatura já

mostrou que jogadores sub-18 foram sujeitos a volumes de treino superiores refletidos

por sessões adicionais de campo e ginásio quando comparados com jogadores sub-16 e

sub-14 (Wrigley et al., 2012). De facto, a progressão das cargas físicas de treino é

crucial para o desenvolvimento da performance física e prevenção de lesões (Matos &

Winsley, 2007). Esta tendência parece reproduzir os princípios de treino defendidos

pelo modelo de preparação desportiva a longo prazo, que sugere cargas de treino

estruturadas de acordo com o estado de maturação do jogador (Balyi & Hamilton,

2004).

http://www.youtube.com/watch?v=NEwkkjvs-C8

1.2. OBJETIVOS E HIPÓTESES

A primeira parte deste estudo teve como objetivo identificar os efeitos agudos que a

adição de sessões específicas de treino de força teve na resposta física, fisiológica e

performance técnico-tática em sessões de treino de Andebol. Neste sentido formularam-

se as seguintes hipóteses:

o O jogo 3x3 induz valores de FC e PSE mais elevados do que o jogo 6x6;

o Os valores da FC e PSE são superiores quando existe TF máxima antecedente;

http://www.youtube.com/watch?v=NEwkkjvs-C8

Capítulo 1 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

53

o A IV diminui após a realização do TF máxima;

o A performance técnico-tática é afetada pelo TF antecedente.

A segunda parte do presente trabalho focou-se na avaliação da carga externa durante

unidades de treino de futebol, através da descrição de perfis de performance e métodos

de classificação dos jogadores. Assim, colocaram-se as seguintes hipóteses:

o O impacto fisiológico das sessões de treino tende a aumentar progressivamente

com a idade.

o As distâncias percorridas em treino pelos jogadores sub-19 são superiores às dos

escalões sub-15 e sub-17;

o Jogadores com idades idênticas apresentam perfis de performance diferentes;

o Agrupar jogadores com perfis físicos e fisiológicos semelhantes reduz a

variabilidade na resposta ao estímulo.

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CAPÍTULO 2

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2.1 ACUTE EFFECTS OF STRENGTH TRAINING IN THE

PHYSIOLOGICAL AND PERCEPTUAL RESPONSE IN HANDBALL SMALL-

SIDED GAMES

Eduardo Abade1, Catarina Abrantes

1, Sergio Ibáñez

2 and Jaime Sampaio

1

1 University of Trás-os-Montes e Alto Douro, Research Center in Sport Sciences,

Health and Human Development (CIDESD). Vila Real, Portugal.

2 Faculty of Sports Science, University of Extremadura.

2.1.1 Abstract

The purpose of this study was to identify the acute effects of different strength training

(ST) programs in perceptual and physiological response to handball small-sided games

(SSG). Twelve senior male players participated in the study (age 22.2 ± 3.4, height 1.82

± 0.05 m, weight 80.6 ± 5.38 kg, BMI 24.4 ± 1.33; HR max 195 ± 10.3). The heart rate

(HR) and the rating of perceived exertion (RPE) were measured during SSG (3x3 and

6x6: 4 blocks of 5 minutes each) in a handball half court, with and without precedent

ST. The results showed that ST increased the time spent above 90% HR max (ST x HR

Zone, p < 0.01) and the RPE during handball SSG (PLAYERS x ST, p < 0.05).

Additionally, the ST induced higher HR and RPE values in SSG 3x3 (PLAYERS x ST

x HR Zone, p < 0.01). Thus, including ST before a SSG training unit increases the

external load and induces higher HR values. Coaches may use ST to increase the

workload during 6x6 games and to develop the aerobic performance during 3x3.

Key words: strength training; heart rate; perceived exertion; small-sided games;

handball.

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2.1.2 Introduction

Team sports performance is the result of a complex and dynamic process, with a high

amount of uncertainty, unpredictability and randomness (Volossovitch, Dumangane, &

Rosati, 2010). Therefore, the players must be able to respond to competition requests, to

manage the disorder resultant from the game constraints and to adapt themselves to

emergent situations of cooperation and opposition (Grehaigne & Godbout, 1998). To

this end, the training units should include constraints involving decision-making, tactics

or techniques that respect the appropriate functional environment (Volossovitch et al.,

2010). In this sense, the small-sided games (SSG) are considered as one of the most

useful drills to be used in the training process, allowing the coaches to manipulate

several variables that can modify the exercise stimulus, such as the number of players or

court size (Hill-Haas, Dawson, Impellizzeri, & Coutts, 2011).

From a physiological standpoint, SSG can induce HR values as high as 90 to 95% of

HR max (Hoff, Wisloff, Engen, Kemi, & Helgerud, 2002). In general, most studies

show that reducing the number of players increase the HR, %HR max, blood lactate

concentrations and perceptual response (Hill-Haas et al., 2011). Other studies have

analyzed the time spent in different intensity HR zones (Gore, 2000) and concluded that

reducing the number of players led to intensity increases, reflected by the time spent

above 90% of HRmax (Hill-Haas, Dawson, Coutts, & Rowsell, 2009) and higher RPE

values (Rampinini, Impellizzeri, Castagna, Abt, Chamari, Sassi, et al., 2007).

Despite the high intensities, similar to those observed in some interval training forms

(Dellal, Chamari, Pintus, Girard, Cotte, & Keller, 2008), the variability of stimulus is

higher in SSG, due to the specific nature of actions inherent to these game formats

(Hill-Haas et al., 2011). In fact, the high intensities and variability of stimulus allow

SSG to include action patterns close to competition requests, since physiological,

technical and tactical demands of the game are always present. Although these results

are useful to understand the physiological demands in SSG, most of the investigations

were performed in soccer. The literature is very scarce in handball and additional

cautions should be taken when using the available results.

Even if SSG are able to faithfully reproduce most of the patterns required to players

conditioning (Impellizzeri, Marcora, Castagna, Reilly, Sassi, Iaia, et al., 2006), the

replication of the muscle demands seems much more difficult. Thus, to benefit from

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significant muscular adaptations, it is necessary to use intense and specific external

loads, only available with specific ST (Zatsiorsky & Kraemer, 2006). In fact, the ST is

essential for achieving high performances during competition (Verkhoshansky, 2006)

and there are several studies showing that ST units are decisive to develop motor

actions such as vertical jump (Luebbers, Potteiger, Hulver, Thyfault, Carper, &

Lockwood, 2003), agility and speed (Miller, Herniman, Ricard, C., Cheatham, &

Michael, 2006).

Concurrent training research describes the effects of combining ST and endurance-

based training, suggesting that residual fatigue occurs following the endurance

component, compromising the ability of muscles to develop tension during the strength

training (Hennessy & Watson, 1994). Probably for these reasons, it is common that

handball high-level teams organize their weekly practices combining ST in a weights

room immediately followed by technical and tactical training in court using SSGs-based

training sessions. However, the available research is unclear due to differences in design

factors such as mode, intensity, frequency of training and training history of subjects.

For example, there is no research describing ST programs with different muscular

solicitations (i.e., focused on upper limbs, lower limbs or both), neither describing their

acute effects on intermittent exercise, such as simulated game situations. In fact,

combining these two components may lead to conflicting physiological adaptations,

endocrine changes or acute fatigue (Leveritt, Abernethy, Barry, & Logan, 1999).

In regard to the acute responses to different ST programs, it seems possible that

different programs might have different effects. For example, a program based on lower

limbs can have an acute effect of impairing the vertical jump and agility during the

game, a program based on upper limbs can have strong acute impact on passing and

goal shots and a program based on both limbs can have both effects and additional

energy expenditure. All these possible single and interactive effects can be indirectly

addressed by the players’ physiological and perceptual responses during SSGs. In fact,

it was already found deterioration on the performance of some technical skills when the

exercise intensity induced RPE values above 15 (Gabbett, 2008). Because sports

performance depends on the ability to performing at high-levels in physical, technique,

decision making and psychological dimensions (Knicker, Renshaw, Oldham, & Cairns,

2011), it is possible that induced fatigue might affect some of these skills, reducing the

performance during team sport games. Despite the important information provided,

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most research was not carried in game-like situations, neglecting the fact that team

sports performance is grounded in the interactions between the individual and the

dynamic constraints of the environment (Araujo, Travassos, & Vilar, 2010).

In essence, there is no available research describing how different ST programs can

influence handball SSGs’ performance. Revealing the acute effects of ST in SSGs

physiological and technical performances, can help handball coaches to optimize the

training process by selecting and combining ST and SSGs according to their best

interest. Therefore, the aim of the present study is to identify the acute effects of

different ST in physiological and perceptual responses to handball small-sided games.

2.1.3 Methods

2.1.3.1 Subjects

The sample included 12 male handball players (age 22.2 ± 3.4, height 1.82 ± 0.05 m,

weight 80.6 ± 5.38 kg, BMI 24.4 ± 1.33; HR max 195 ± 10.3). All subjects were part of

the same team with seven training units per week (5 handball sessions lasting for 90

minutes and two ST lasting for 60 minutes) and competed in 30 matches per season. A

briefing session took time where it was presented to the players a disclosure document

with all the procedures, benefits and risks associated with participation in this study. All

of them were notified that they could leave the study at any time. This protocol was

approved by the ethics committee of the Research Center in Sports Sciences, Health and

Human Development.

2.1.3.2 Design

The protocol familiarization took place in distinct stages by using ST with external

loads of approximately 50% to 60% of 1 RM (Hakkinen, Pakarinen, Kraemer, Newton,

& Alen, 2000) that included all ST exercises, 33 and 66 in a handball half court (400

m²). Both HR and RPE were monitored in these sessions.

The following week began with the first data collection session (UPPER + SSG 33).

During UPPER, the six players participating in this first part of the study were grouped

in pairs to perform the sequence of a circuit with four stations. The groups organization

allowed a player to rest while the other was performing the exercise, optimizing

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recovery times (Zatsiorsky & Kraemer, 2006). The rotary system provided to all

individuals the same recovery time between the last strength exercise and the beginning

of the SSG 33.

After UPPER, a 20 minutes interval was allowed to set HR monitors on each subject.

After this break, the players performed the 33 SSG (4 blocks of 5 minutes each) with

alternated functions between the attack and defense. At the end of the 4th block, the HR

monitors were gathered and all players filled the RPE values on a printed sheet of paper

to facilitate their decision (Coutts, Rampinini, Marcora, Castagna, & Impellizzeri,

2009). After a period of 72 hours from the first data collection (UPPER + SSG 33), the

protocol was repeated in SSG 33 with no ST. In the three following weeks, the

procedure was identical, only with a different type of ST preceding the SSG. The weeks

5, 6 and 7 followed the same organization and procedures of weeks 2, 3 and 4, however,

the SSG were played in 66. The ST with 12 subjects had exactly the same

methodology and organization.

All SSG took place in an indoor sports court with a total area of 400m² (half court

handball), however, 74.5m² belong to the goalkeeper area, which makes a playable area

of approximately 325.5m². The SSG were played according to the International

Handball Federation (IHF) official rules and the ball used was from size three for senior

males (60cm and 475g - IHF). Several balls were placed at the playing area perimeter so

that it could be immediately restored when leaving the bounding lines (Kelly & Drust,

2009).

2.1.3.3 Methodology

The dependent variables were the time spent in four zones of %HR max and RPE

values. The ST and handball SSG were the independent variables. The ST type was

divided in four intervention levels: no strength training (NONE), strength training for

upper limbs (UPPER), strength training for lower limbs (LOWER) and strength training

for upper and lower limbs (TOTAL). The type of SSG had two levels: SSG 33 and

SSG 66.

Individual HR monitors (Polar Team System, Polar, FI) were used to record HR

continuously during SSG (33 and 66) and to measure HRmax by performing the Yo-

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Yo Intermittent Endurance Test - Level 2 (Bangsbo, 1996). After the implementation of

the protocol, HR data was downloaded to the Polar Precision Performance SW -

Version 4.01.029 and later exported to a spreadsheet where it was grouped in four zones

of %HR max (Gore, 2000): Zone 1 (<75%), Zone 2 (≥ 75% - 84.9%), Zone 3 (≥ 85% -

89.9%) and Zone 4 (≥ 90% - 100%). To determine the maximum dynamic strength the

test of one maximum repetition (1RM) was performed on different days (Brown &

Weir, 2001) for each strength exercise.

During the protocol application, all types of ST were carried according to the

hypertrophic methodology (Zatsiorsky & Kraemer, 2006) with 3 sets of 10 to 12 RM,

low speed execution (4-5 seconds per repetition) and recovery periods of approximately

60 seconds. The perceived exertion was measured by using the Borg Perceived Exertion

Scale (6-20) (Borg, Hassmen, & Lagerstrom, 1987).

2.1.3.4 Statistical Analysis

Data are expressed as means (±S.D). The RPE and technical variables were analyzed

with a 24 repeated measures ANOVA: number of players (33 or 66) and strength

training situation (NONE, UPPER, LOWER, TOTAL). To analyze HR data, the zone

repeated factor (with 4 levels) was included in the model, resulting in a 244 repeated

measures ANOVA. Eta squared values were used as effect sizes. All analyses were

performed using Statistica software version 8 (Statsoft, Tulsa USA) and the significance

level was maintained at 5%.

2.1.4 Results

The table 2.1 presents the results of simple effects comparisons and interactions

between the number of players (33 and 66), types of ST (NONE, UPPER, LOWER

and TOTAL) and time spent in the four HR zones. Also, table 2.1 shows the results of

simple effects comparisons and interactions between the number of players (33 and

66) and types of ST (NONE, UPPER, LOWER and TOTAL) to the RPE values.

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Table 2.1. Comparing the time spent in HR zones and RPE values according to the

number of players and type of ST.

Simple effect/Interaction F p Ƞ2 Power

HR

PLAYERS 0.0 0.972 - -

ST 4.2 0.013* 0.27 0.81

HR ZONE 7.2 0.001* 0.40 0.97

PLAYERS ST 0.1 0.980 - -

PLAYERS HR ZONE 14.9 0.000* 0.58 1.00

ST HR ZONE 2.9 0.004* 0.21 0.95

PLAYERS ST HR ZONE 6.5 0.000* 0.37 1.00

RPE

PLAYERS 78.2 0.000* 0.88 1.00

ST 9.2 0.000* 0.46 0.99

PLAYERS ST 3.3 0.032* 0.23 0.70

* Significant difference between conditions (p<0.05)

The ST HR ZONE interaction identified higher values of time spent in zone 4 when

there was ST. The players spent more time in HR zones 1 and 2 without ST (Fig.2.1a).

Figure 2.1b represents the PLAYERS ST HR ZONE interaction. In 33 SSG, ST

(UPPER, LOWER and TOTAL) did not decrease the time spent at the highest intensity

HR zone (Z4, ≥90 – 100%). Regardless of precedent type of ST, players spent more

time in HR zones 1 and 2 during SSG 66. The PLAYERS ST interaction analysis

shows that the SSG 33 induced greater RPE values than SSG 66. At both SSG, RPE

values were higher when there was precedent ST (Fig. 2.1c).

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Figure 2.1. ST x HR ZONE interaction to the time spent in each one of the four HR

zones (a); PLAYERS x ST x HR ZONE interaction to the time spent in each one of the

four HR zones (b 3x3, b 6x6); PLAYERS x ST interaction to RPE values (c).

2.1.5 Discussion

The purpose of this study was to identify the acute effects of different ST programs in

perceptual and physiological response to handball small-sided games. In general, the

results showed that ST induced higher HR and RPE values in both SSG. The results

also suggest that, during SSG 33, the ST did not decrease the time spent in HR zones

of highest intensity (above 85%HR max). Additionally, the responses identified in 66

SSG presented increased variability.

Our results showed that after the ST, SSG 33 elicited greater HR and RPE values than

those verified in SSG 66. SSG with a reduced number of players seem to induce higher

physiological stimulus, probably due to the larger ratio area per player and the superior

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number of ball contacts. Thus, it is possible that the addition of ST resulted in an

additional muscular stimulus, reflected by the higher values of HR and RPE during SSG

33. Available research, mainly in soccer, presents several factors that may contribute

to increase intensity in SSG, such as the reduction of players number (Capranica,

Tessitore, Guidetti, & Figura, 2001), the greater interaction of the players with the ball

and the opponents (Hill-Haas et al., 2009), the increase of individual technical and

tactical actions and the higher distance travelled with the ball (Katis & Kellis, 2009).

Research focused on the analysis of specific soccer motor skills during SSG (33 and

66) found that the sprint, agility and horizontal jump performances decreased after

both SSG, but mainly in 33 (Katis & Kellis, 2009). The difficulty to perform some of

these motor tasks can be related to the fatigue induced by SSG with a reduced number

of players (Katis & Kellis, 2009). These results confirm that playing handball 33 SSG

elicits a superior physiological stimulus than playing 66. Therefore, SSG 33 can be

used as an important drill to improve the aerobic performance in game context.

In the current results, the addition of ST did not decrease the time spent above 85%

HRmax and the RPE in both SSG. Despite the SSG format, it is possible that the

muscular fatigue induced by ST affected the performance of some motor skills and that

might resulted in higher physiological strain during SSG. Together, the stimulus of both

ST and SSG can elicit neuromuscular mechanisms that might be a handicap to perform

some handball speed, agility and vertical jump based drills. Several studies have found

increases in muscle fatigue immediately after ST with high loads (McCaulley, McBride,

Cormie, Hudson, Nuzzo, Quindry, et al., 2009). It was also verified that ST (70% of

1RM) induced muscular fatigue and decreased muscular torque five minutes after the

training (Ferri, Narici, Grassi, & Pousson, 2006), however, there were not significant

changes in muscle activation and voluntary electromyography activity. This fact may

suggest that peripheral mechanisms play a key role on reducing the muscular strength.

The decrease in the ability to generate power is also justified by the increasing

concentrations of blood lactate during the ST with high intensities (Kraemer,

Marchitelli, Gordon, Harman, Dziados, Mello, et al., 1990). In this context, it has

already been observed an increase in blood lactate concentration of about 10 to 13

mmol/L during a hypertrophic ST (Mero, Leikas, Knuutinen, Hulmi, & Kovanen,

2009).

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Handball is mainly characterized by high intensity but short duration skills, as sprints

and vertical jumps (Rannou, Prioux, Zouhal, Gratas-Delamarche, & Delamarche, 2001).

However, these kind of specific actions are dependent on the ability to generate power

in lower limbs muscles, particularly on the knee extensors, hip extensors and plantar

flexors (Frick, Schmidtbleicher, & Stutz, 1995). Muscle fatigue, high lactate

concentrations and the reduction of muscle torque, seem to lead to lower agility, speed

and jumping ability. Therefore, the current results suggest that ST may contribute to

increase exercise intensity, which supports the higher values of RPE and the time spent

above 85% HR max, as seen when ST preceded SGG. Although under different

conditions, concurrent training research has also found higher HR values in aerobic

interval exercise, when performed after strength training (Alves, Saavedra, Simão,

Novaes, Rhea, Green, et al., 2011).

Our results identified increased variability during 66 SSG, suggesting higher and less

predictable inter-player differences for the same exercise. The SSGs with a higher

number of players resulted in a decrease of individual contacts with the ball and,

therefore, the physiological pattern becomes more intermittent, e.g., the high intensity

actions are interspersed with low intensity actions with less predictable durations.

Contrarily to the intermittent running exercises, the players’ activity during SSG cannot

be controlled by coaches, as there are factors which influence the physiological

responses and promote these heterogeneous intensities (e.g., the inclusion of

goalkeepers (Dellal et al., 2008), number of contacts with the ball (Capranica et al.,

2001), running without the ball (Katis & Kellis, 2009), the specific positioning and the

opponents behavior (Stolen, Chamari, Castagna, & Wisloff, 2005)). In fact, the higher

variability in SSGs when compared to intermittent run exercises was already identified

(Dellal et al., 2008).

The issue of selecting the most compatible level of ST in combination with the used

SSGs is complex. One of the first physiological adaptations to exercise is the

catecholamine responses, which can influence skeletal muscle force and metabolic

activity (Fry, Kraemer, Vanborselen, Lynch, Triplett, Koziris, et al., 1994). Also, the

mechanisms of fatigue are related to several metabolic factors (e.g. adenosine

triphosphate, inorganic phosphate, phosphocreatine, lactate), diminished glucose or

glycogen availability, ionic factors (e.g. K+, Na + , Ca2+, Cl - ), acidosis (Fitts, 1994),

hypoxia (Amann, Romer, Pegelow, Jacques, Hess, & Dempsey, 2006), reactive oxygen

Capítulo 2 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

82

species and/or ultrastructural damage (Byrne, Twist, & Eston, 2004). In single terms

and probably interactively, the symptoms underlying these mechanisms are peripheral

and central fatigue, afferent feedback, diminished time to exhaustion, increased RPE,

impaired motor skill outcomes and decision-making (Knicker et al., 2011). Therefore,

from the current results, it might be possible to suggest that 3x3 SSG seems to promote

intensities above 85% HR max regardless of the preceding ST (UPPER, LOWER,

TOTAL). The 6x6 SSG, however, does not seem to induce high intensities when there

was no preceding ST. In this case, the TOTAL ST was the most effective in increasing

intensity.

In addition, our results show that players spent more time in lower HR zones (<75% and

≥75% - 84.9%) when there was no ST. It is possible that the lower muscular stimulus

may be a handicap to reach similar intensities to those verified in competition. Handball

games can elicit average %HRmax values of 85% (Loftin, Anderson, Lytton, Pittman,

& Warren, 1996), thus the lack of ST can compromise, mainly in 66, the replication of

significant physiological demands in SSG.

All ST levels (UPPER, LOWER and TOTAL) were able to promote high HR and RPE

values, therefore, ST in general can be used to reach high intensities in training. Adding

together, HR and RPE values show that the SSG implies high physiological loads,

especially when there is precedent ST.

2.1.6 Conclusion

The main findings of this study demonstrate that the ST can influence the overall

intensity during SSGs. For example, the inclusion of a ST before a SSG training unit

increases the external load and induces higher HR values than those verified in SSG

without precedent ST. Despite of the high intensity verified at both SSG, the 33 format

provided higher HR values. Thus, coaches can use ST as a useful tool to induce higher

intensities during training sessions, enabling the development of aerobic performance in

a game situation. When using SSG 66, coaches should consider the TOTAL program

as more effective to increase the physiological stimulus. However, the possibilities of

other ST methods induce different effects to those found in this study, requires further

research. The data collected from this investigation may provide useful information to

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83

coaches, helping them to organize and plan microcycles that includes co-existence of

SSG and ST.

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CAPÍTULO 3

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3.1. ACUTE EFFECTS OF STRENGTH TRAINING PROGRAMS ON THE

VERTICAL JUMP AND TECHNICAL ACTIONS IN HANDBALL DURING

PRESEASON

Eduardo Abade1, Bruno Gonçalves

1, José Vilaça

1 and Jaime Sampaio

1



3.1.1. Abstract

The aim of this study was to identify the acute effects of hypertrophic strength

training programs on the vertical jump and technical actions in small-sided handball

games during preseason. 12 senior male players (M age = 22.2 yr., SD = 3.4)

participated in 3x3 and 6x6 small-sided games preceded by no strength training or

upper limbs/ lower limbs/ upper + lower limbs strength training. The results showed

that strength training can affect the vertical jump performance and the effectiveness of

some skills towards the end of the small-sided games duration. The higher

physiological stimuli during 3x3 promote the deterioration of some skills’ proficiency,

mainly during small-sided games with preceding strength training. The 6x6 elicits

higher cooperation and interaction between players and potentiates the vertical jump

performance after strength training.

Key words: strength training; preseason; vertical jump; technical skills; small-sided

games; handball.

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3.1.2. Introduction

Handball is characterized by repeated accelerations, sprints, jumps and repeated changes

of direction that involve a great amount of body contact between players. Such demands

may affect the physical performance of players during competition, elicit high fatigue

and increase the risk of injury (Zebis, Bencke, Andersen, Alkjaer, Suetta, Mortensen, et

al., 2011). Muscle strength and power in the pelvis, upper, and lower extremities are

determinant factors in specific handball actions such as the jump throw (Wagner,

Pfusterschmied, Tilp, Landlinger, von Duvillard, & Muller, 2012). Strength training is a

key factor to obtain high level performance and it is essential to developing the vertical

jump (Luebbers, Potteiger, Hulver, Thyfault, Carper, & Lockwood, 2003). However,

adequate inclusion of strength training in the annual cycle of handball training is a

complex issue, due to the diversity of contents to be trained in a concentrated

competitive schedule (Verkhoshansky, 2006). Apparently, to promote maximum

performance and to diminish the possibility of injury, most strength training loads

should be in the first half of the preseason (Bompa, 1993). For team sports like

handball, the goal of strength training should be the development of the muscle strength

and strength endurance during the preseason (Issurin, 2010), immediately before the

maximum strength adaptations (Bompa, 1993).

Hypertrophic training is commonly used to promote structural changes in the muscle

morphology and cross sectional area that support greater gains in muscle strength

(Verkhoshansky, 2006). However, these structural changes are slower than neural

adaptations (Sale, 1988), which may be a constraint when planning a handball

preseason that usually lasts from four to six weeks. The preseason training demands for

high volume and diversified exercises to develop physical and technical abilities in a

short period of time (Issurin, 2010). Therefore, coaches should cautiously organize their

weekly schedule to prevent for conflicting physiological responses.

The performance in handball can be measured with scoring (e.g., goals) and

performance indicators (e.g., successful or unsuccessful passes) (Hughes & Bartlett,

2002) during small-sided games. These situations can be manipulated to influence

physiological, technical, and tactical stimuli (Hill-Haas, Dawson, Impellizzeri, &

Coutts, 2011) and allow for functional movement behaviors to emerge (Pinder, Davids,

& Renshaw, 2012). Small-sided games seem to increase the frequency of technical

actions, specifically when performed with a small number of players (Hill-Haas, et al.,

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91

2011). Additionally, the variability of stimuli allows small-sided games to include

action patterns similar to competition requests, since physiological, technical, and

tactical demands of the game are strongly replicated. Therefore, small-sided games are

vital to the development of skills in game-like situations and to optimize the training

process during the preseason. However, small-sided games do not appear to provide

significant muscle demand, i.e., specific external loads that induce considerable

neuromuscular adaptation (Zatsiorsky & Kraemer, 2006). Consequently, the preseason

should include both small-sided games and strength training to maximize the players’

technical and physical performance.

Strength training is essential for improvement of critical handball motor actions such as

the vertical jump (Marques & Gonzalez-Badillo, 2006). Vertical jump ability has been

related to muscle contractile mechanisms, maximal force capacity, rate of force

development, muscle coordination, and the stretch-shortening cycle (Rimmer &

Sleivert, 2000). These neuromuscular patterns reproduced during the vertical jump

performance can be found in handball-specific defensive (e.g., blocking) and offensive

movements (e.g., jump shots). Therefore, the vertical jump is recognized as a useful

index of the muscular ability to generate power and can be used to monitor performance

as well as to provide important information about the functional ability of lower limbs

under different conditions (Quagliarella, Sasanelli, Belgiovine, Moretti, & Moretti,

2010). Regardless of the recent investigation of the acute effects of strength training

(Babault, Kouassi, & Desbrosses, 2010) and acute fatigue in response to handball match

play (Thorlund, Michalsik, Madsen, & Aagaard, 2008), the available literature does not

describe the effects of strength training programs with different muscular solicitations

(i.e., focused on upper limbs, lower limbs or both) on players’ performance in game-like

situations. Additionally, there is no research relating the acute effects of combining both

strength training and small-sided games in technical and vertical jump performance

during a handball preseason. Such information could provide coaches important

information for planning short-term programs including both small-sided games and

strength training. Therefore, the goal of the present study is to identify the acute effects

of different strength training in the skill and vertical jump performance to handball

small-sided games.

Hypothesis 1. A significant decrease in the vertical jump performance is expected

immediately after the strength training.

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92

Hypothesis 2. Greater deterioration of the vertical jump is expected after 3x3 small-

sided games.

Hypothesis 3. Maximum strength training is expected to impair technical performance

during small-sided games.

3.1.3. Method

3.1.3.1.Participants

Twelve male senior handball players who competed in the Portuguese second division

volunteered to participate in this study. All participants were part of a team with an

average of eight hours of training per week (M age = 22.2 yr., SD=3.4; M height =1.82

m, SD = 0.05; M weight 80.6 kg, SD = 5.38; M BMI = 24.4, SD = 1.33; M HR max =

195 bpm; SD = 10.3). The participants agreed with the protocol description and were

aware of its benefits and risks. They were also notified that they could withdraw from

the study at any moment without any penalty. The study protocol was conformed to the

declaration of Helsinki and was approved by the ethics committee of the Research

Center in Sport, Health and Human Development (Vila Real, Portugal).

3.1.3.2.Procedures

The strength training type was divided in four levels: no strength training, upper limbs

strength training (Upper), lower limbs strength training (Lower) and upper and lower

limbs strength training (Total). The small sided games were performed in two formats:

GK + 3x3 and GK + 6x6 in a handball half court. The maximum dynamic strength (1

maximum repetition, 1RM) was assessed for each exercise (Upper: Horizontal bench

press, Deltoid press, Pullover, and Wrist flexion; Lower: Squat, Leg Curl, Lunge, and

Plantar flexion) (Brown & Weir, 2001). The Total strength training included two

exercises from both Upper and Lower (Horizontal bench press, Squat, Plantar flexion

and Wrist flexion).

The strength training protocol was performed according to the hypertrophic methods

with 3 sets of 10 to 12 maximal repetitions at a low speed execution (5 sec. per

repetition) and recovery periods of 60 sec. (Zatsiorsky & Kraemer, 2006). To measure

vertical jump height, the participants performed the squat jump, counter movement

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93

jump and abalakov jump (Bosco, Luhtanen, & Komi, 1983). The jumping height (m)

was calculated with an Ergojump (Bosco System, Globus, Italy). All games were

recorded with a standard camcorder and the reliability of notational analysis was

inspected by calculating kappa (ĸ) coefficients. Four weeks before the protocol

application, there was an anthropometric and dynamic maximum strength evaluation. In

the following week, all participants were familiarized with the protocol procedures. The

notational analysis of technical skills was held experimentally by the observers during

the protocol familiarization. A chronological schedule of the protocol is presented in

table 3.1.

Table 3.1. Chronological schedule that preceded the protocol application.

Week 1 Week 2 Week 3 Week 4 Week 5

Protocol

presentation

Anthropometric

characterization

HR max

evaluation

Maximum

dynamical strength

evaluation

Protocol

familiarization

Protocol

6 weeks Presentation of

protocol contents

and standards.

Weight, Height

and BMI

assessment

yo-yo

Intermittent

Endurance

Test (Level 2)

1 RM evaluation

SSG 33; SSG

66; UPPER;

LOWER;

TOTAL; VJ

Note. SSG = small sided games; Total = upper and lower limbs strength training; Upper

= upper limbs strength training; Lower = lower limbs training; VJ= Vertical jump.

The first data collection (3x3 + Upper) started with stretching and a low intensity run (7

km / hr.) on a treadmill for warm-up. Afterwards, the players performed two attempts

for each vertical jump protocol with a 10-sec. break. The best jump value was recorded.

After this first vertical jump evaluation (Pre strength training, PRE ST), a 5-min. rest

interval was given before initiating Upper strength training. The strength training was

done on a rotary system with four stations, to optimize the recovery time between

exercises and to provide the same recovery time from the last strength training exercise

to the beginning of the 3x3 small-sided game. A second vertical jump evaluation took

place immediately after Upper strength training (post strength training, POS ST),

followed by a 20-min. interval. After this break, a 3x3 small-sided game was performed

with teams alternating attack and defense per block. Small-sided games were divided in

four blocks of 5 min. (1st half, 1st and 2nd blocks; 2nd half, 3rd and 4th blocks) with 2-

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94

min. inter-game intervals (20 minutes of effective activity). The players were divided

(following the instructions of the head coach) into two balanced teams according to

their ability in passing, ball control, and game sense (Hill-Haas, et al., 2011).

Immediately after the small-sided games, the vertical jump was evaluated for the third

and last time (Post small-sided games, POS SSG). In that same week, after a 72-hour

interval, the protocol was repeated without strength training.

In the two following weeks, the protocol respected the exactly same procedure but in

this case, the strength training units that preceded the 3x3 were Lower and Total

strength training conditions, respectively. In Weeks 4, 5, and 6 the protocol was the

same, however, strength training and 6x6 small-sided games were performed with 12

participants, so four players took part in each one of the strength training stations. The

small-side games took place in an indoor court with a total area of 400 m² (325.5 m² of

playable area). The games were played according to the International Handball

Federation official rules and the ball used was size three for senior males (60 cm

diameter, 475 g). To avoid intensity disruptions, all penalty infractions were considered

as goals to the attacking team. In addition, to prevent subjectivity in rules interpretation,

a single referee was selected and maintained during the whole protocol. The offensive

actions were recorded within three shooting zones (Zone A: area between the midfield

and 9-m line; Zone B: central zone area between the 9- and 6-m lines; Zone C: wing

shooting zone). All actions were assigned to ball possessions and analyzed using the

percentage per 100 ball possessions.

3.1.3.3.Measures

The notational analysis of offensive technical actions included passes and catches (with

and without success), set shots and jump shots (with and without success) and technical

errors. The interceptions and goalkeeper actions were the considered defensive actions.

Data reliability was high (ICCs above .90).

3.1.3.4.Analysis

The data are presented as means and standard deviations. All data sets from technical

indicators and vertical jump performance were assessed for outliers and assumptions of

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95

normality. A repeated-measures ANOVA was performed to identify inferential

differences in vertical jump performance (PRE ST, POS Stand POS SSG) according to

the number of players, type of strength training, and time of testing effects. When

appropriate, the Scheffe post-hoc test was used for multiple comparisons. Effect size

was presented as eta squared form (mean, [95% confidence intervals]). The vertical

jump performance was also presented as percentage of height variation, with the Pre

strength training (PRE ST) performance being considered as the baseline.

All analyses were performed using Statistica Version 8 (Statsoft, Tulsa USA) and alpha

was set at .05.

3.1.4. Results

The vertical jump values according to the number of players, type of strength training

and time of testing are presented in Fig. 3.1. Significant differences were found in the

triple interaction between the time of testing, number of players, and strength training

(table 3.2). Also, differences were identified in the single effect of time of testing, in the

interaction between time of testing and number of players. Overall, the vertical jump

performance decreased after all types of strength training, with higher values after the

6x6 small-sided games. However, Figs. 3.1 , 3.2 and 3.3 show that after 3 small-sided

games there was a decrease in vertical jump performance when the game was preceded

by Upper or Lower strength training.

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96

Figure 3.1. Results from interaction Players x Strength Training x Time for squat jump

values. LOWER (lower limbs strength training); POS SSG (after small sided games);

POS ST (after strength training); PRE ST (before strength training); TOTAL (upper and

lower limbs strength training); UPPER (upper limbs strength training).

Figure 3.2. Results from interaction Players x Strength Training x Time for counter

movement jump values. LOWER (lower limbs strength training); POS SSG (after small



training).

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97

Figure 3.3. Results from interaction Players x Strength Training x Time for abalakov

jump values. Legend: LOWER (lower limbs strength training); POS SSG (after small



training).

Table 3.2. Analysis of Variance to Assess Differences in Vertical Jump Performance by

Number of Players in Small-sided Games, Type of Strength Training, and Time of

Testing.

Source MSE F df p 2

mean, [95% CIs]

Time of testing (T)

SJ 0.0125 48.8 22 <.001 0.82, [0.61, 0.88]

CMJ 0.0090 34.1 22 <.001 0.76, [0.50, 0.84]

AJ 0.0105 67.6 22 <.001 0.86, [0.70, 0.91]

T x Players (P)

SJ 0.0016 7.5 22 <.01 0.41, [0.07, 0.59]

CMJ 0.0022 8.3 22 <.01 0.43, [0.08, 0.61]

AJ 0.0026 10.1 22 <.001 0.48, [0.13, 0.64]

T x P x Strength training

SJ 0.0016 9.1 44 <.001 0.45, [0.18, 0.57]

CMJ 0.0001 3.3 44 <.05 0.23, [0.01, 0.37]

AJ 0.0013 5.1 44 <.001 0.32, [0.06, 0.46]

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98

According to Fig. 3.4, the percent change in vertical jump performance from baseline,

recorded after the 6x6 small-sided games (POS SSG), were lower than those after

strength training (POS ST). Compared to baseline, the vertical jump performance

increased after 6x6 small-sided games when there was precedent Upper and Lower

strength training. However, after the 3x3 games there was a decrease from the vertical

jump baseline after Upper strength training (squat jump and countermovement jump)

and Lower strength training (countermovement jump and abalakov jump).

Figure 3.4. Percentage (%) of the height variation from the baseline (PRE ST) to the

interaction Players x Strength Training x Time.

The 6x6 games promoted a higher percentage of passes than the 3x3 games (17.21±5.14

of successful and 0.59±0.22 of unsuccessful versus 9.33±2.10 of successful and

0.24±0.18 of unsuccessful, respectively). Also, the 6x6 games elicited a higher

percentage of successful catches than the 3x3 (17.10±5.25 and 9.15±1.93, respectively).

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99

The percentage of unsuccessful set shots was higher in 3x3 compared to those verified

in 6x6 (0.64±0.31 and 0.33±0.19, respectively).

Furthermore, significant differences were identified in the percentage of technical errors

between 3x3 and 6x6 games when there was Total strength training (0.12±0.08 and

0.01±0.01, respectively). The percentage of interceptions was higher in the 6x6

(0.41±0.21) compared to those occurred in the 3x3 (0.10±0.09). The percentage of

goalkeeper actions increased in the second half of both SSG (first half, 0.95±0.33;

second half, 1.34±0.51) and it was higher when there was precedent Upper (1.45±0.67)

and Lower strength training (1.21±0.43). Finally, the number of players influenced the

number of shots per shooting zone, with a higher number of shots in the wingers’

position (zone C) being recorded in 3x3 small-sided games (28.08±12.28 and

12.84±3.77).

Table 3.3. Analysis of Variance to Assess Statistical Differences in % of Technical

Actions by Number of Players in Small-sided Games, Type of Strength Training and

Half (only statistical significant differences are presented).

3.1.5. Discussion

The results showed that vertical jump decreased after all types of strength training,

probably justified by the neuromuscular process, elastic and contractile capacity of the

Source MSE F df p 2

mean, [95% CIs]

Number of players

Passes (successful) 16.775 28.5 16 <.001 0.64, [0.27, 0.78]

Passes (unsuccessful) 0.0421 24.7 16 <.001 0.61, [0.23, 0.76]

Catches (successful) 17.230 27.3 16 <.001 0.63, [0.26, 0.77]

Set shots (unsuccessful) 0.0605 16.3 16 <.001 0.51, [0.12, 0,69]

Interceptions 0.0347 22.4 16 <.001 0.58, [0.20, 0.74]

Half

Goalkeeper actions 0.0831 11.9 16 <.01 0.69, [0.28, 0.79]

Number of players x Strength training

Technical errors 0.0006 3.65 16 <.05 0.41, [0.00, 0.59]

Strength training Half

Goalkeeper actions 0.0285 4.1 16 <.05 0.43, [0.00, 0.61]

Capítulo 3 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

100

muscle structure (Komi, Nicol, & Marconnet, 1992) and to the present study

hypertrophic strength training methodology. In fact, this strength training methodology

can increase blood lactate concentrations up to 10 to 13 mmol (Mero, Leikas,

Knuutinen, Hulmi, & Kovanen, 2009), impair the muscular contraction and the acute

capacity of the stretch shortening cycle to generate muscular torque (Rodacki, Fowler,

& Bennett, 2002). These symptoms play a crucial role on the reducing of the lower

limbs strength power, which may support the deterioration of the vertical jump

performance after strength training units.

The results showed that vertical jump absolute values increased after 6x6 games when

compared to the POS ST values. Previous studies have demonstrated that high-threshold

fast motor units are recruited during maximal intensity actions such as vertical jump

(Kubo, Morimoto, Komuro, Tsunoda, Kanehisa, & Fukunaga, 2007). In fact, vertical

jump height is considered an important indicator of the lower limbs muscle power and it

has been used to assess the lower extremity function and to measure the power

development because of its high reproducibility (Slinde, Suber, Suber, Edwen, &

Svantesson, 2008). Also, strength training research has shown that performing maximal

(or near maximal) muscular contractions can produce short-term increases in maximal

force due to phosphorylation of myosin light chains resulting from the initial muscle

activity and excitability of alfa-motoneurons resulting in a greater contractile

performance after previous muscular activity (Sweeney, Bowman, & Stull, 1993). Thus,

it seems that maximal voluntary contractions can improve the acute muscle peak torque

and the explosive muscle performance. In contrast, vertical jump capacity was impaired

after 3x3 with precedent Upper strength training (squat and counter movement jumps)

and Lower strength training (countermovement and abalakov jumps). One of the

possible reasons is that small-sided games with a higher number of players have lower

physiological impact because the addition of players lowers %HRmax, blood lactate

concentrations and perceived exertion (Hill-Haas, et al., 2011). The strength training

using high loads promotes acute muscular fatigue, however, it was already found that

after a 60-min. hypertrophy strength training, lactate concentrations and the ability to

generate force returned to levels close to those recorded before the strength training

(McCaulley, McBride, Cormie, Hudson, Nuzzo, Quindry, et al., 2009). The time gap

between the strength training and game situations, the apparently recovery of the ability

to generate power and the stimulus elicited by 6x6, may have resulted in the

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101

potentiating of the vertical jump performance. Indeed, the agility, sprint and jump

capacity decline after playing a soccer 3x3 game (Hill-Haas, et al., 2011). Considering

that sprint capacity depends on the stretch-shortening cycle muscle function of upper

and lower musculature and its relation with vertical jump height (Maulder & Cronin,

2005), the general impairment of the vertical jump performance after 3x3 with

preceding strength training may be explained by the decrease of both limbs muscle

power. Interestingly, despite of the importance acknowledged to lower limbs when

performing jumping actions, upper extremity strength is also important in jump throws,

due to difficulties to use trunk rotation or lower extremity force (Fleck, Smith, Craib,

Denahan, Snow, & Mitchell, 1992). Apparently, the high intensity promoted by 3x3

resulted in vertical jump decreases and did not allow recovering from fatigue induced

by Upper and Lower strength training.

The 6x6 small-sided games promoted more successful and unsuccessful passes,

successful catches and interceptions, suggesting higher interaction between the players

for the same playable area. The higher number of passing possibilities in 6x6 has

facilitated the occurrence of successful catches and passes. On the other hand, it appears

that the reduction of the ratio area per player and the consequent proximity between

players has provided a higher number of unsuccessful passes and interceptions.

Opposing to the small-sided games with a reduced number of players that seem to

decrease the available choices for the player with ball, the 6x6 games appear to facilitate

the cooperation between players. Previous research has found that the addition of

players increased the number of skills per team, while reducing the number of players

has been related to the increase of individual contacts with the ball (Hill-Haas, et al.,

2011). The small-sided games with smaller number of players reduced the solutions to

the player with the ball and consequently, the possibilities of cooperation. As a

consequence, the tendency of the player to solve the constraints using individual

solutions increases. Adding together, it is possible that the higher physiological stimulus

and the increase of individual actions promoted by 3x3 games may not allow sustaining

the technical skill proficiency. In fact, the present study showed that the number of

unsuccessful set shots was higher in 3x3, which supports the idea that high intensity

game situations may be counterproductive in terms of playing performance.

The number of shots in the wingers’ zone (zone C) was higher during 3x3, suggesting

that players tend to search for unoccupied areas in the lateral corridors when the number

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102

of players is lower. In fact, it was already showed that small-sided games with a smaller

number of players require different tactical requirement (Hill-Haas, et al., 2011). The

greater distances travelled when the ratio area per player is higher, turn out the game

pattern to be more unpredictable. In accordance to previous research (Hill-Haas, et al.,

2011), it may be suggested that the relationship between the individual workout profiles

and the skills performance should be the target of future investigations to help clarifying

these results.

The 3x3 with precedent Total strength training induced a higher number of technical

errors. The high intensity exercises like strength training and small-sided games with a

smaller number of players can increase the peripheral and central fatigue, impair the

motor skills outcomes and decision-making (Knicker, Renshaw, Oldham, & Cairns,

2011). Adding together, these fatigue related symptoms seem to affect the skill

performance as it is shown by the increase of technical errors verified in current study

when the 3x3 small-sided games was preceded by Total strength training. Additionally,

the acute muscular fatigue elicited by the Lower and Upper strength training may have

affected the lower and upper limbs capacity to generate power during both SSG, which

supports the higher occurrences of unsuccessful jump shots.

Apparently, high-duration small-sided games decrease the number of consecutive

contacts with the ball, suggesting that as game progresses, players tend to solve the

constraints using less individual solutions. In the final 15 minutes of a soccer game, the

peak sprinting speed can be hampered (Bangsbo & Mohr, 2005) and replacement

players can perform 25% more high-intensity running and 63% more sprinting (Mohr,

Krustrup, & Bangsbo, 2003). These fatigue manifestations can deteriorate the technique

execution and the throwing velocity (Knicker, et al., 2011), which explains the

increased number of goalkeeper actions in the final moments of the small-sided games

with preceding strength training (mostly after Upper and Lower).

Short-term planning in team sports requires that coaches understand the acute effects of

combining strength and technical-tactical training. This study provided new evidences

on how strength training may be combined with court training (small-sided games). The

vertical jump capacity is impaired after maximum strength training. Comparatively to

the moment immediately following strength training, the vertical jump height increases

after 6x6, but is impaired after 3x3 with precedent Upper and Lower strength training.

The high intensity promoted by 3x3 does not allow recovering from fatigue induced by

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Upper and Lower strength training, probably due to the decrease of both limbs muscle

power. The higher physiological stimuli during 3x3 promote the deterioration of some

technical skills proficiency, mainly during high duration small-sided games with

preceding strength training. The 6x6 elicits a higher cooperation and interaction

between players and potentiates the vertical jump performance after strength training.

Coaches usually consider the preseason as a specific period to develop technical-tactical

skills but also to increase the players’ muscle mass. These findings highlight the

importance of selecting adequate court training exercises after a hypertrophic strength

training session.

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104

3.1.6. References

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CAPÍTULO 4

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4.1. TIME-MOTION AND PHYSIOLOGICAL PROFILE OF FOOTBALL

TRAINING SESSIONS PERFORMED BY UNDER 15, UNDER 17 AND UNDER

19 ELITE PORTUGUESE PLAYERS


1, Nuno Leite

1 and Jaime Sampaio

1



4.1.1. Abstract

The aim of this study was to provide time-motion and physiological profiles of football

training sessions (TS) performed by under 15, under 17 and under 19 elite level

Portuguese players. 151 elite players of under 15 (age 14.0±0.2 n=56), under 17 (age

15.8±0.4 n=66) and under 19 (age 17.8±0.6 n=29) participated in the study during a 9-

week period. Time-motion and body impact data were collected using GPS technology

(15Hz) with heart rate monitored continuously (1Hz) across 38 randomly selected TS

that resulted in a total of 612 samples. The total distances covered (m) were higher in

U17 (4648.3±831.9), followed by U19 (4212.5±935.4) and U15 (3964.5±725.4) players

(F=45.84, p<.001). Total body impacts and relative impacts were lower in U15 (total:

490.8±309.5, F=7.3, p<.01), but no differences were identified between U17 (total:

584.0±363.5) and U19 (total: 613.1±329.4). U19 players had less high/very high

intensity activity (F=11.8, p<.001) and moderate intensity activity (F=15.07, p<.001).

The heart rate values showed significant effects of zones (F=575.7, p<.001) and

interaction with age groups (F=9.7, p<.001) with pairwise differences between all

zones. All players spent most of time below 75% HRmax. Results showed high

variability between training sessions, refraining from identifying meaningful trends

when measuring performance, although, different demands were identified according to

the age groups. The U15 TS were less physiologically demanding, probably caused by

increased focus on small-sided games to develop basic tactical principles and technical

skills. The focus on game like-situations imposed a higher external and internal

workload on U17 and U19 players.

Key words: age groups; workloads; youth football

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109

4.1.2. Introduction

The identification of key performance indicators in football is important to improve the

training process among youths. Football is an intermittent team sport that includes both

high and low intensities with mean and peak heart rates between 69% and 91% of

maximal values, respectively1. Also, short-term training field periods can elicit average

HR values (b.min-1

) of 135±5, 151±4 and 151±5 in U18, U16 and U14 age groups2. The

variability and unpredictability of the game is reflected in accelerations, decelerations,

changes of direction and in the execution of several technical skills, all of them having a

strong effect in energy expenditure3. For these reasons, the training drills should include

different physiological stimuli to provide optimal adaptations4. If the training process is

exclusively directed to the development of technical and tactical skills, the intensity and

the variability of the physiological stimulus could be compromised. Thus, in order to

promote an effective transfer to the competitive environment, it is suggested that the

sport-specific training must provide the inclusion of technical and tactical abilities in

similar conditions to those which occurs during the match play5. In essence, the

stimulus intensity is a key variable that influences the training response and should be

carefully considered when short and mid-term plans are designed.

Describing the intensity of training can provide valuable information for adjusting the

training stimulus to the players’ specific needs6. The study of important variables such

as the number of sprints performed, high-intensity running and total distance covered7,

can contribute for a better understanding of the performance during a game or training

session. The total distance covered by youth players during a match is approximately

6311 meters (ranging from 4435 to 8098m) with 12% comprising high intensity

activities1. The analysis of these movement patterns can be useful to study the activity

profiles of players8, however, football is a contact sport that requires the performance of

other specific actions such as tackles and jumps9. From this point of view, literature is

scarce describing the body impacts experienced by football players, either in training or

game situation. An accurate determination of the G forces experienced by football

players might help to better understand the competition physical demands10

. Moreover,

adding physiological variables such as the heart rate to these work-rate profiles can be

helpful in understanding the oscillations in players’ performance during training drills.

Heart rate monitoring has been regularly used to assess the intensity during training and

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110

game situations and it has been recognized as a valid indicator to quantify physical

demands9.

The available research in football time-motion and physiological responses is mostly

focused in competition demands and disregards the training sessions (TS). In fact, there

seems to be a clear need to have reference values regarding the physical demands

according to different age groups in TS. The availability of such data can help coaches

to support daily planning by selecting task constraints that may optimize the players’

performance development. Therefore, the aim of this study was to describe the time-

motion and physiological profile of TS performed by under 15, under 17 and under 19

elite level Portuguese players.

4.1.3. Methods

4.1.3.1.Subjects

The sample included 151 elite young Portuguese football players of under 15 (three U15

teams, n=56), under 17 (four U17 teams, n=66) and under 19 (two U19 teams, n=29)

age groups (see table 4.1). The players belong to five different elite youth teams that

were competing in the national championship (2011/2012 season). The participants,

their parents and coaches agreed with the protocol description and were notified that

they could withdraw from the study at any moment. This protocol was conformed to the

declaration of Helsinki and was approved by the ethics committee of the Research

Center in Sports Sciences, Health and Human Development (Vila Real, Portugal). The

sample size was calculated with G*Power (Version 3.1.5.1 Institut für Experimentelle

Psychologie, Düsseldorf, Germany) for an effect size of 0.4, an α of 0.05, and a power

of 0.8 (1-β). The total sample size computed by this method was 66, i.e., a minimum of

22 subjects in each group.

Table 4.1. Description of players’ sub-samples.

U15 (n=56) U17 (n=66) U19 (n=29) F p Post-hoc

Age (years) 14.0±0.2 15.8±0.4 17.8±0.6 4137.9 <.001 a,b,c

Height (m) 1.71±0.07 1.76±0.06 1.77±0.07 46.5 <.001 a,b

Weight (kg) 60.1±6.3 65.8±5.5 70.0±5.6 170.1 <.001 a,b,c

BMI (a.u) 20.4±1.2 21.2±1.4 22.4±1.0 154.5 <.001 a,b,c

Experience (years) 5.4±1.2 6.8±1.7 9.0±1.7 312.5 <.001 a,b,c

Significant differences are identified as: (a) U15 vs. U17; (b) U15 vs. U19; (c) U17 vs. U19.

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111

4.1.3.2.Design

The study was conducted during the competitive season over a 9-week period

(December to February) and 38 randomly chosen TS (U15 n=12, U17 n=16 and U19

n=10) representing a total of 612 cases. All the practice sessions were performed at the

same time period of the day (from 16.30h to 21.00h) on natural turf pitches, under

similar environmental conditions (temperature 14–19°C, relative humidity 52–66%).

Both U15 and U17 teams trained in the same 60x40 meters on an outdoor pitch (4 TS

per week with an average duration of 90 minutes), while U19 teams trained in an

outdoor pitch with official dimensions (5 TS per week with an average duration of 90

minutes). For each age group, all TS were continuously performed in the same pitch.

Besides the regular physical education classes, none of the players was involved in

some other sport activity. The average number of players per training unit was 23±4.

4.1.3.3.Methodology

All practice sessions started with low intensity running and ball possession drills for

warm up and ended with a standardized cool down consisting of stretching exercises.

Players were allowed to consume water during a specific training session recovery

period (approximately 3 minutes). The goals of the TS differed among the age groups.

The clubs and coaches authorized to perform only a comprehensive general description

of practice sessions’ used drills. TS were mainly based on constrained small-sided

games according to each age group technical, tactical and physical aims. The U15 TS

mainly included the development of technical skills and elementary tactical principles.

Although the specific goals of U17 practices remained similar to U15, there was an

increased focus in game-like situations. The U19 TS included constrained small-sided

games focused on team tactical principles and physical conditioning stimulus. Players

were allowed to consume water during a specific TS recovery period (approximately 3

minutes).

The time motion variables were collected with 20 GPS units working at a sampling

frequency of 15Hz (SPI-Pro X II, GPSports, Canberra, Australia). Although the validity

and reliability of 10 Hz devices were already inspected by independent verifications11

,

no validation study has been done for 15Hz units. The variables recorded were the

relative distance covered per minute (m.min-1

), the total distance covered (m) and the

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112

distances at different speed zones12

: zone 1 (0-6.9 Km.h-1

), zone 2 (7.0-9.9 Km.h-1

),

zone 3 (10.0-12.9 Km.h-1

), zone 4 (13-15.9 Km.h-1

), zone 5 (16-17.9 Km.h-1

) and zone 6

(≥18.0 Km.h-1

). Sprints (zone 6) were also measured by number, average time interval

and average distance covered. Additionally, three ratios were calculated in order to

relate distance covered at high/very high (above 16 Km.h-1

), moderate (10.0-15.9 Km.h-

1) and low-intensity (7.0-9.9 Km.h

-1) with distance covered at very low intensities (0-6.9

km.h-1

) normalized for each 100 meters for comparison purposes. These work:rest

related ratios are frequently used in the literature to describe the activity profiles13,14

.

The heart rate (HR) data were recorded continuously with individual monitors (Polar

Team System, Polar, FI) and grouped into four zones of %HRmax15

: zone 1 (<75%),

zone 2 (75% - 84.9%), zone 3 (85% - 89.9%) and zone 4 (≥ 90%). To measure the

players’ HRmax, the Yo-Yo intermittent recovery level 2 test was performed16,17

. Also,

the GPS devices are coupled with a 100 Hz tri-axial accelerometer which allowed the

estimation of body impacts18

. This variable was grouped into six zones of G force10

:

Zone 1 (< 5.0–6.0g), Zone 2 (6.1-6.5g), Zone 3 (6.5-7.0g), Zone 4 (7.1-8.0g), Zone 5

(8.1-10.0g) and Zone 6 (> 10.1g). Also, the relative impacts per minute and the total

impacts performed (independently of the zones) were recorded. The GPS and the HR

devices were attached to the players and activated 15 minutes before the beginning of

each training session, according to the manufacturer guidelines. The analysed TS had

different durations, therefore, all the data was normalized to 60 minutes of training time.

4.1.3.4.Statistical Analysis

The data are presented as means ± standard deviations. The mean intersection

coefficient of variation (%) was obtained across all considered variables according to

the age groups. A one-way ANOVA was performed to identify the differences in total

and relative distance covered, body impacts and workout ratios across the age groups.

The sprint activity variables were tested using non-parametric Mann-Whitney U tests.

Three repeated measures factorial ANOVA models were performed to identify

differences in time motion (6 zones x 3 age groups), heart rate (4 zones x 3 age groups)

and body impact zones (6 zones x 3 age groups) according to the age groups. Pairwise

differences and post-hoc comparisons were tested with Bonferroni post-hoc test.

Finally, a non-parametric independent sample Kruskal-Wallis test was performed to

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113

identify the differences in coefficient of variation (%) according to the age groups19

. All

data sets were tested for each statistical technique corresponding assumptions. These

calculations were done SPSS Software (version 18.0, Chicago, Illinois, USA). The

statistical significance was maintained at 5%.

4.1.4. Results

The table 4.2 presents the results from distance covered, sprint characterization and

impacts across age groups. The total and relative distances covered presented significant

differences between age groups (F=40.2, p<.001). The number of sprints (activity

performed above 18 Km.h-1

) were different between U15 and U17 (10.9±6.3 and

16.4±8.2, z=-7.2 p<.001, respectively) and between U17 and U19 (16.4±8.2 and

11.8±7.9, z=-5.1 p<.001, respectively). The average time interval presented differences

between U19 and both U15 (z=-2.2, p<.05) and U17 (z=-2.6, p<.01). Also, the average

distance covered for each sprint was significant higher (z=-2.6, p<.01) in U17 than in

U19 (13.0±5.3 and 11.8±6.7, respectively). In addition, the total impacts and relative

impacts presented statistical differences (F=7.3, p<.01) between U15 and the other two

age groups. No differences were found between U17 and U19.

Table 4.2. Analysis of distance covered, sprint characterization and body impacts

across age groups.

Variables U15 U17 U19 Post-hoc

Distance covered (m)

Total 3964.5±725.4 4648.3±831.9 4212.5±935.4 a,b,c

Relative (m.min-1

) 66.1±12.1 77.5±13.9 70.2±15.6 a,b,c

Sprint

Number 10.9±6.3 16.4±8.2 11.8±7.9 a,c

Time interval per sprint (s) 2.1±0.8 2.3±0.9 2.1±1.2 b,c

Average distance covered per sprint (m) 12.1±4.9 13.0±5.3 11.8±6.7 c

Body Impacts (number)

Total 490.8±309.5 584.0±363.5 613.1±329.4 a,b

Relative (impacts.min-1

) 8.2±5.2 9.7±6.1 10.2±5.5 a,b

Significant differences are identified as: (a) U15 vs. U17; (b) U15 vs. U19; (c) U17 vs. U19.

The figure 4.1a presents the variation of distance covered at the considered speed zones

for each group. There was a significant effect of speed zones (F=6495.5, p<.001,

Capítulo 4 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

114

2=.92, Power=1.00), with pairwise differences between all zones. Also, the interaction

between speed zones and players’ age groups was significant (F=22.1, p<.001, 2=.07,

Power=1.00). The heart rate values (see figure 4.1b) showed significant effects of zones

(F=575.7, p<.001, 2=.49, Power=1.00) and interaction with age groups (F=9.7, p<.001,

2=.03, Power=1.00) with pairwise differences between all zones. The players spent

most of time below 75% HRmax. The Figure 4.1c presents the number of impacts in the

six considered G force zones. There was a significant effect of zone (F=1936.6, p<.001,

2=.76, Power=1.00) with pairwise differences in all zones. Additionally, differences

were found (F=4.8, p<.01, 2=.02, Power=1.00) between U15 and U17 and between

U15 and U19. The players performed a higher number of impacts in zone 1 (<5.0–6.0g).

Finally, the figure 4.1d presents the distance covered at high/very high, moderate and

low speed zones for each 100 meters covered in the very low-activity zone. The results

showed significant differences in the high/very high intensity activity (F=11.8, p<.001)

and moderate intensity activity (F=15.07, p<.001), between U19 and both U17 and U15.

No differences were found in low/very low activity.

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115

Figure 4.1. Results from distance covered for each speed zone (a), time spent in each

heart rate zone (b), number of impacts for each intensity zone (c) and distance in

different intensity zones for each 100m covered at very low intensity (d).

The table 4.3 presents the mean intersection coefficient of variation (%) between age

groups. Significant differences were found (p<.05) in distances covered for zones 1, 5

and 6 between U17 and U19. HR presented significant differences (p<.05) for zones 2

and 3 between U15 and U19. Also, the variability in the number of sprints performed

was different (p<.05) between U17 and U19.

Table 4.3. Mean intersection Coefficient of variation (%) according to the age groups.

Variables U15 U17 U19 Post-hoc

Distance covered

Zone 1 16.28 12.63 16.06 b

Zone 2 29.75 37.05 25.36 -

Zone 3 33.73 38.90 34.12 -

Zone 4 37.75 36.83 43.10 -

Zone 5 44.10 32.80 52.12 b

Zone 6 64.60 47.33 67.52 b

Total 17.33 16.83 19.58 -

Heart Rate

Zone 1 33.10 36.18 35.36 -

Zone 2 36.68 35.63 40.36 a

Zone 3 46.18 47.05 73.76 a

Zone 4 78.05 77.70 105.66 -

Sprint

Number 57.20 42.98 69.16 b

Time interval 32.13 30.58 39.42 -

Distance covered 34.18 32.13 40.76 -

Impacts zone

Zone 1 53.28 55.33 48.60 -

Zone 2 65.28 62.53 57.00 -

Zone 3 73.93 68.75 59.40 -

Zone 4 80.00 75.13 69.24 -

Zone 5 91.03 94.45 86.04 -

Zone 6 127.48 126.65 127.44 -

Total 61.45 59.25 56.80 -

Significant differences are identified as: a) between U15 and U19; b) between U17 and U19.

4.1.5. Discussion

This study aimed to describe time-motion and physiological profiles of TS performed

by under 15, under 17 and under 19 players competing in the Portuguese national

championship. Previous research has been exclusively focused on monitoring specific

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116

moments of practice sessions or drills in highly controlled situations using constrained-

tasks20

. However, in order to improve ecological validity it seems important to monitor

and describe the total physiological workload imposed by the regular training process

without any external manipulation.

Results showed high variability between training sessions, refraining from identifying

meaningful trends when measuring performance but, alternatively, it might also be

consider that this variability is functional and constitutes a key-characteristic of elite

training sessions21

. The distances covered for all age groups confirm the diversity of

stimulus promoted during a football practice session, probably by including technical,

tactical and physical drills with diverse aims, variable intensity and volume loads9. The

coefficient of variation (%) according to age groups showed higher values in distances

covered, HR and number of sprints for U19 players. Probably, the focus on team tactical

principles required additional coaching intervention, promoting more task interruptions

across the training sessions and eliciting variability. Consequently, the lower effect sizes

across variables may also be linked to this high variability. Nevertheless, the focus on

constrained small-sided games to develop basic tactical principles and technical skills

during U15 TS probably promoted a more regular activity pattern and resulted in the

lowest variability among the age groups.

The results of the present study suggest coaches to establish short and mid-term

planning guidelines corresponding to elite demands in youth football players.

Unfortunately, only a comprehensive description of practice sessions’ tasks could be

carried. Thus, the impossibility of manipulating the training contents implies caution on

the practical application of the results. Yet, the general idea from the results points that

football game-based training in these age groups has different consequences. Although

speculative, it is likely that the U15 training is less physiologically demanding, probably

because of the time spent in learning technical skills and basic tactical principles in

short-dimension pitches. The U17 age group gathers players with increased biological

maturation, capable of responding to higher power and speed demands during the

frequent game-like situations. Finally, the U19 constrained small-sided games focused

on team tactical principles may be linked to the decrease of the physiological demands.

Still, considering different age groups may have impaired an accurate control of the

players’ maturational status.

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117

The external load was already described according to playing positions by using

distances covered during match-play22

and running velocities in treadmill protocols23

.

Although it is known that the physiological demands may vary according to playing

position24

, available literature does not clarify the variations that might exist both

among different age groups and during training situations. The short term planning of

the three age groups was established by coaches, based on technical and tactical needs

in each one of the age groups. The U15 TS were mainly focused on constrained small-

sided games directed to the development of the basic tactical principals and technical

skills, which can help justifying the lower distance covered. These training guidelines

are in accordance with the long-term athlete development plans for this age group,

reinforcing the importance of deliberate practice based on targeted and task centred

training programs25

.

Comparatively to U15, the use of frequent game-like situations during U17 and U19 TS

can support the higher covered distances. In particular, the U17 players covered the

highest total and relative distances and had the highest number of sprints. The use of

game-like situations played with fewer constraints helped to increase physiological

stimulus. On the other hand, the small-sided games training used in U19 practice

sessions might have more stopping times to adjust the teams’ tactical model. In fact, the

U19 high/very high:very low and moderate:very low work ratios presented the lowest

values. This lack of high intensity activity may compromise the replication of the

physiological pattern required in elite competition, as described by early available

research7,9,26

.

In all age groups, the players covered higher distances in the first four speed zones

(between 0-6.9 km.h-1

) and players spent the highest amount of time below 75%

HRmax. A previous study focused on the distances covered at different running speeds

during a young football match found that players covered the highest distances between

0-6.0 km.h-1

and the lowest above 21.1 km.h-1

22

. However, the time spent above 180

b.min-1

intervals was higher than below 180 b.min-1

22

. Although the external load

imposed on young players during training is similar to those verified during a match

play, the average HR values during matches is substantially higher than those found in

practice sessions. In the U17 and U19 sessions, the frequent use of game like situations

elicited a higher number of sprints. The use of constrained small-sided games aiming to

the basic tactical principles and technical development during U15 TS resulted in lowest

Capítulo 4 ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

118

distances covered below 9.9 km.h-1

. Thus, coaches should be aware that the replication

of the competition physiological pattern may be compromised if TS do not include more

game-like situations to promote higher intensities and variability13,27,28

.

Although football is an invasion team sport with frequent contact, the activity profile

does not seem to promote a high occurrence of impacts. In the current study, the

average number of total impacts identified during the football-TS was of 471±291.5,

563±350.7 and 572±325 for U15, U17 and U19 players, respectively. Of interest is,

however, the significant difference identified between the U15 practices and the other

groups. In fact, when game situations are frequently used, the higher occurrence of

specific football actions such as changes of directions29,30

may increase the number of

impacts and consequently the strength and power demands.

4.1.6. Practical Applications

High variability between training sessions can be a key-characteristic of elite

teams’ training sessions.

The constrained small-sided games used to develop the basic tactical principles

and technical skills during TS promoted a decrease of the physiological

demands. In order to promote an increase in external and internal workload,

coaches should frequently use game like situations.

Youth football coaches can use these reference data to establish accurate short

and mid-term planning guidelines corresponding to elite demands in youth

football players for practice sessions.

4.1.7. Conclusion

The high variability between training sessions might refrain from identifying

meaningful trends, however, it might also be consider that this variability is functional

and constitutes a key-characteristic of elite training sessions. The external load imposed

on players differed in accordance with the age group. The U15 TS promoted less

physiological demands because of the focus on the small-sided games aiming to the

development of basic tactical principles and technical skills. Conversely, the frequency

of game like-situations was higher during U17 and U19 sessions that imposed a higher

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119

and more variable external load to the players. In addition, the use of game situations

during football TS seems to increase the number of impacts, resulting in activity

patterns that is more similar to the competition requirements. From a practical point of

view, coaches seem to be aware of the importance of the technical abilities development

at earlier age stages. Also, more game situations are promoted as biological maturation

increases. As the age groups progress, football coaches may plan the TS more similar to

the formal game physical, technical, and tactical demands.

Acknowledgements

This study was supported by PTDC/DES/098693/2008 project: “Evaluating training and

competition in team sports. Aggregating tactical analysis, external and internal

workload” financed by the Portuguese Foundation for Science and Technology (FCT).

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4.1.8. References

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typical weekly in-season training load in elite junior soccer players. J Sport Sci.

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5. Williams AM, Hodges NJ. Practice, instruction and skill acquisition in soccer:

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9. Bangsbo J, Mohr M, Krustrup P. Physical and metabolic demands of training

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11. Castellano J, Casamichana D, Calleja-Gonzalez J, San Roman J, Ostojic SM.

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Strength Cond Res. 2012.

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22. Aslan A, Acikada C, Guvenc A, Goren H, Hazir T, Ozkara A. Metabolic

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soccer players in the French first league - with special reference to their playing

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CAPÍTULO 5

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5.1. HELPING COACHES TO CLASSIFY YOUNG FOOTBALLERS

ACCORDING TO THEIR TRAINING PERFORMANCES


1, Alexandra Silva

1, Nuno Leite

1, Carlo Castagna

2

and Jaime Sampaio1



2 Football Training and Biomechanics Laboratory, Italian Football Federation (FIGC),

Technical Department, Coverciano (Florence), Italy.

5.1.1. Abstract

This study aimed to classify young footballers according to their physical and

physiological profiles in training sessions (TS) and to contrast this classification

procedure against the age and playing position criteria. 151 male elite football players of

under 15, under 17 and under 19 years old stages participated in this study over a 9-

week period. Time-motion and body impact data were collected using GPS technology

with heart rate monitored continuously across 38 randomly selected TS. The results

demonstrated that players with identical ages and playing experience may have very

different performance profiles. This method may provide helpful criteria to group

players and diminishes the variability of the physiological outcomes, allowing coaches

to have an accurate control on players’ responses.

Key words: football, cluster analysis, performance profiles.

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125

5.1.2. Introduction

The competition in many youth team sports is organized according to several age

groups, mostly because of the need to enhance educational and fair-play values.

Although generally accepted, this organization form may fail to consider differences in

chronological age, since players within the same age group can have very distinct

physical and physiological profiles (Cobley, Baker, Wattie, & McKenna, 2009).

The identification and description of these profiles may provide valuable information to

refine the training workloads, task designs and environmental constraints. During

adolescence, the playing positions and selection level (i.e., Regional, National) have an

important interactive effect in players’ characteristics (Till, Cobley, O'Hara, Chapman,

& Cooke, 2012). In fact, most motor skills experience significant developments during

the pubertal period, reinforcing the importance of specific training (Fernandez-Gonzalo

et al., 2010). Therefore, the coaches should regularly track the progression of players’

responses to training and competition, considering the interaction between ages and

playing positions.

From a physiological perspective, understanding the development of athletic potential

alongside biological growth is crucial to select appropriate training aims at different

stages of players’ development. The long-term athlete development models generally

encourage the use of a wide range of activities in the earlier ages with a progressive

narrowing of sport focus in more advanced ages (Côté & Fraser-Thomas, 2007).

However, aiming for the most sensitive development periods seems to be a very delicate

issue, partly because the long-term effects of youth intensive training and competitive

schedules are poorly explored by literature.

To develop a successful sports career, young players have to perform adequately in

several dimensions (Elferink-Gemser, Visscher, Lemmink, & Mulder, 2004). Generally,

the training sessions have a strong focus on game like situations, eliciting both dynamic

and adaptive responses, providing high variability of physiologic, technical and tactical

stimulus (Pinder, Davids, & Renshaw, 2012). However, the manipulation of constraints

can be quite limited because, even if the task constraints contain relevant information

for learning a specific activity, the unique characteristics of each learner also represent

personal constraints (Chow et al., 2006). In fact, it is possible to identify that individual

learning dynamics will be different since the interacting configurations of constraints

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126

will differ between learners (Chow, Davids, Hristovski, Araujo, & Passos, 2011).

Consequently, when physiological profiles vary among players, caution should be

applied in data interpretation, mainly because of the differences in emergent behaviors.

Therefore, it is dysfunctional to establish universal optimal learning pathways to which

all learners should adhere. The presence of instabilities in the perceptual-motor

landscape related to differences in growth, development, maturation and learning might

provide qualitative changes in their performance (Hristovski, Davids, Araujo, & Passos,

2011).

Within the available literature, the activity profiles of young football players are usually

described in relation to playing positions (Aslan et al., 2012; Buchheit, Mendez-

Villanueva, Simpson, & Bourdon, 2010) and age groups (Fernandez-Gonzalo et al.,

2010; Till et al., 2012). For example, it was showed that running performance tends to

increase with age (Buchheit et al., 2010) and youth players cover from 4435 to 8098m

during a match (Rebelo, Brito, Seabra, Oliveira, & Krustrup, 2012). The players seem to

cover the highest distances in low speed zones (0-6.0 km.h-1

) and the lowest above

21.1km.h-1

(Aslan et al., 2012). The distances covered vary according to playing

positions, with defenders and midfielders achieving the lowest and highest distances,

respectively (Buchheit et al., 2010). The defenders seem to have lower endurance

performances than midfielders and forwards (Markovic & Mikulic, 2011).

The differences in movement and activity patterns require for different conditioning and

recovery programs according to age and positional groups (Quarrie, Hopkins, Anthony,

& Gill, 2012) because football demands for hard accelerations and decelerations,

changes of direction and collisions. Therefore, the players’ body impact activity and HR

profiles will help to better understand and assess the physical demands as well as to

adjust rest and recover times after training and matches (Quarrie et al., 2012). High-

level players are frequently required to perform high intensity sprints and changes of

direction which underlines agility as a key ability (Sheppard & Young, 2006).

Consequently, the development of changing direction related mechanisms, such as the

sprinting capacity (Jones, Bampouras, & Marrin, 2009), power and strength qualities is

a major issue to coaches and considered an important predictor of performance (P.,

Chan, & Smith, 2012).

All these variables seem important to describe the players’ physiological profile and to

provide key information to adjust the training load. However, these were really never

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127

contrasted against the players’ actual internal load in training. The data gathered in

training sessions can also be used to classify the players into different groups of

performance, alternatively to different groups of ages and playing positions. In fact,

physiological variables are suggested to be powerful predictors to identify talent in

youth sports (Unnithan, White, Georgiou, Iga, & Drust, 2012). In this sense, the

classification techniques (e.g., cluster analysis) based on physiological profiles may

provide useful information for establishing groups of interest for talent identification

and training prescription.

Therefore, the aim of this study was to classify young footballers according to their

physical and physiological profiles in training sessions and to contrast this classification

procedure against the age and playing position criteria. In addition, we aimed to identify

the most powerful variables in players’ classification. The improvements in these

classification procedures will allow the sports clubs and coaches to improve the

accuracy of training plans and the improvement in players’ interactions along the

training tasks.

Hypothesis 1. It is expected to find different performance profiles among players with

identical ages and playing experience.

Hypothesis 2. We hypothesized that heart rate values and body impacts would represent

the most powerful predictors to discriminate performance profiles in training.

5.1.3. Method

5.1.3.1.Participants

One hundred and fifty-one male football players of under 15 (U15 n=56), under 17

(U17 n=66) and under 19 (U19 n=29) years old stages participated in this study. The

participants were part of five different elite youth teams, training and competing

regularly in the Portuguese national competition (2011/2012 season). After a detailed

protocol explanation about the aims, benefits and risks involved in this investigation, all

participants, parents and coaches signed a written informed consent. Additionally,

players were informed that they were free to withdraw from the study at any time

without any penalty. The study protocol was conformed to the declaration of Helsinki

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128

and was approved by the ethics committee of the Research Center in Sport, Health and

Human Development (Vila Real, Portugal).

5.1.3.2.Procedures

The study was conducted during the competitive season over a 9-week period

(December to February) with 38 randomly chosen training situations (U15 n=12, U17

n=16 and U19 n=10) representing a total of 612 cases. All the practice sessions were

performed at the same time period of the day (from 16.30h to 21.00h) in outdoor natural

turf pitches, under similar environmental conditions (temperature 14–19°C, relative

humidity 52–66%). Both U15 and U17 teams trained four times per week for a total of

360 minutes in a 60x40 meters pitch, while U19 teams trained five times per week for a

total of 450 minutes in a pitch with official dimensions. Besides the regular physical

education classes, none of the players was involved in other sports. The average number

of players per training unit was 23±4.

All practice sessions started with a specific warm up that included low intensity running

and ball possession drills. Stretching exercises were performed at the end of each

training session. Players were allowed to drink water during specific recovery periods

were allowed (approximately 3 minutes). The clubs and coaches authorized to perform

only a comprehensive general description of practice sessions’ used drills. All sessions

began with a ~15 minute warm-up and ended with ~10 minutes of cool down exercises.

The U15 training sessions mainly included the development of technical skills and

elementary tactical principles. Although the specific goals of U17 practices remained

similar to U15, there was an increased focus in game-like situations. The U19 training

sessions included constrained small-sided games focused on team tactical principles and

physical conditioning stimulus.

The players’ external workload was represented by the median values from all

monitored training units. The distance covered was measured in predefined speed zones

(Aguiar, Botelho, Goncalves, & Sampaio, 2012): zone 1 (0.0-6.9 km.h-1

), zone 2 (7.0-

9.9 km.h-1

), zone 3 (10.0-12.9 km.h-1

), zone 4 (13.0-15.9 km.h-1

), zone 5 (16.0-17.9

km.h-1

) and zone 6 (≥18.0 km.h-1

). Sprints (zone 6) were also measured by both average

time interval and distance covered. The data were collected at 15Hz through the entire

duration of each training sessions using portable global positioning system units (SPI-

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129

PRO X II, GPSports, Canberra, ACT, Australia). These units were fitted to the upper

back of each participant using an appropriate elastic harness. The validity and reliability

of these instruments were already inspected by independent verifications for the both 5

and 10Hz units (Castellano, Casamichana, Calleja-Gonzalez, San Roman, & Ostojic,

2011; Johnston et al., 2012).

Players’ internal workload included the HR and the body impacts variables. The HR

absolute values were recorded continuously throughout all training sessions using the

Polar Team System (Polar Electro, Oy, Kempele, Finland) and, subsequently, converted

into percentages of HRmax and classified into time spent in four zones of intensity

(Gore, 2000): Zone 1 (<75% HRmax), Zone 2 (75-84.9 % HRmax), Zone 3 (85-89.9 %

HRmax) and Zone 4 (≥ 90 % HRmax). To measure the players’ HRmax, the Yo-Yo

intermittent recovery level 2 test was performed (Krustrup et al., 2006). The SPI-PRO X

II units are coupled with a 100Hz accelerometer capable of measuring the body impacts

thought the rate of acceleration and deceleration ability in horizontal axis (x), transverse

axis (y) and vertical axis (z). This variable measures the changes of direction, collisions

with opposition and the ground. The values were grouped into six zones of G force

(McLellan, Lovell, & Gass, 2011): zone 1 (very light impact, <5.0–6.0g), zone 2 (light

to moderate impact, 6.1-6.5g), zone 3 (moderate to heavy impact, 6.5-7.0g), zone 4

(heavy impact, 7.1-8.0g), zone 5 (very heavy impact, 8.1-10.0g) and zone 6 (severe

impact, >10.1g).

5.1.3.3.Analysis

A two-step cluster with log-likelihood as the distance measure and Schwartz’s Bayesian

criterion was performed to classify athletes according to their performance profiles (i.e.

all variables described in procedures section). The considered analysis was used to point

out physical and physiological similarities among players. This method differs from

traditional clustering techniques by handling of categorical variables (assuming

variables to be independent), automatic selection of number of clusters (automatically

determines the optimal number of clusters) and scalability (by constructing a cluster

membership) (Tabachnick & Fidell, 2007). The variables were ranked according to their

predictor importance, indicating the relative importance of each predictor in estimating

the model (the sum of the values for all predictors on the display is 1). Subsequently,

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the clustering variables description was presented as means ± standard deviations. The

sprint activity variables were tested using one-way ANOVA. Finally, a repeated

measures factorial ANOVA was performed to identify differences in time motion, HR

and body impact zones according to the clustering groups. Pairwise differences were

assessed with Bonferroni post-hoc test. All data sets were tested for each statistical

technique corresponding assumptions. These calculations were carried in SPSS

Software (v20.0, IBM Corporation, USA) and statistical significance was maintained at

.05.

5.1.4. Results

The cluster analysis classified the players into three distinct groups in accordance with

their physical and physiological performances during the training sessions. The obtained

clusters comprised, respectively, 15.2%, 37.1% and 47.7% of the total sample size. No

differences were found in players’ age, height, weight, BMI and experience between the

clusters (see table 5.1).

Table 5.1. Characterization of the cluster groups.

Cluster 1 (n=23) Cluster 2 (n=56) Cluster 3 (n=72)

Age 15.7±1.5 15.4±1.0 15.5±1.7

Height 1.72±0.06 1.76±0.07 1.74±0.07

Weight 63.2±5.6 65.1±6.2 64.5±7.7

BMI 21.3±1.4 21.0±1.3 21.2±1.6

Experience 6.5±1.9 6.8±1.7 6.7±2.3

The figure 5.1 shows the distribution (%) of players in each Cluster considering the

players’ actual development stage and playing position. The Cluster 1 presents the

lowest percentage of sample size, with a high presence of U19 midfielders,

comparatively with the other age groups and playing positions. The Cluster 2 includes

the highest percentage of U17 players and the lowest percentage of U19 players. The

Cluster 3 is the group with higher size. The percentage of U15 forwards and defenders

is high, as well as U19 midfielders and defenders.

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131

Figure 5.1. Distribution (%) of players in each cluster considering the players’

development stage and playing position

Sprints characteristics (activity performed above 18 km.h-1

) presented differences

between clusters 2 and 3 for both time interval (F=11.7, p<.001) and distance covered

per sprint (F=11.6, p<.001). The cluster 3 presented the lowest average time interval

(1.67±0.24 seconds) and distance covered per sprint (9.45±1.43 meters).

The figure 5.2 presents the results from both external and internal workload across

clusters and also the predictor importance (PI) from all considered variables. Figure 5.2i

presents the variation of distance covered at the considered speed zones for each cluster.

There was a significant effect of both speed zones (F=2573.3, p<.001, η2=.95) and

clusters (F=3.3, p<.001, η2=.43). Also, differences were found in body impacts zones

(F=1020.8, p<.001, η2=.87) and clusters (F=44.1, p<.001, η

2=.37), with pairwise

differences across all groups, except between clusters 2 and 3 for zone 6 (see figure

5.2ii). The HR zone values showed significant effect of zones (F=487.1, p<.001,

η2=.77) and clusters (F=30.9, p<.001, η

2=.30) with players spending most of the time

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below 75% of HRmax (see figure 5.2iii). Finally, figure 5.2iv presents the obtained

predictor importance from the variables. The strongest PI was found in body impacts for

zones 5 (PI=1.00), 3 (PI=0.88), 4 (PI=0.85) and 2 (PI=0.85). Distance covered at zone 1

was identified as the lowest PI (PI=0.03).

Figure 5.2. Results from distance covered for each speed zone (i), number of impacts

for each intensity zone (ii) time spent in each heart rate zone (iii) and predictor

importance to all considered variable (iv). Significant differences are identified as: (a)

Cluster 1 vs. Cluster 2; (b) Cluster 1 vs. Cluster 3; (c) Cluster 2 vs. Cluster 3

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5.1.5. Discussion

This study aimed to identify the most powerful performance predictors in clustering

young footballers during training sessions, providing more accurate information about

the players’ response to training stimulus. The obtained clusters were very similar in

aging, anthropometric characteristics and experience years. This similarity suggests that

these variables may not be the most important to discriminate the performance profiles

in training. In general, the current results demonstrated that players with identical ages

and playing experience might have very different physiological profiles and,

consequently, respond in different ways to similar training stimulus. Some predictors

such as anthropometric and physiological characteristics have recently been suggested

to identify talent in youth sports and may represent useful information to predict future

career progression (Unnithan et al., 2012). Thus, the clustering methods can provide

performance profiles to enable early identification of talented youths. Also, grouping

players with similar physiological characteristics may diminish the emergence of

heterogeneous responses during training, which can help coaches in the distribution of

training groups and allow an efficient control on the players’ response. Moreover,

clustering may be performed by using valuable information from fitness tests, which

allow coaches to manipulate these profiles in any moment of the competitive season.

The current results identified that body impacts in higher intensity zones (zones 2 to 5)

were the predictors that best discriminated the obtained clusters. Although the training

tasks were similar across all age groups, the players’ responses in body impacts varied

substantially across the clusters. This importance may suggest that selected task

constraints in training enhance a specific learning, exhibited in players’ unique rates of

acceleration and deceleration. Sprints with changes of direction seem to induce a higher

neuromuscular stimulus than intermittent in-line sprints (Dellal et al., 2010), mostly

because of its high relationship with the eccentric strength (Jones et al., 2009). The

results show that players in cluster 1 performed a higher number of impacts across all

zones. This analysis may help coaches to identify the most capable players to

successfully perform high intensity and rapid body movements. It seems that these data

is important to understand and measure the performance indicators of the high intensity

intermittent exercises, frequently experienced during training and/or game situations

(Vaz, Leite, Vicente, Gonçalves, & Sampaio, 2012). These results present a new insight

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to the process of monitoring training effects, by including body impacts as key variable

to understand the players’ individuals’ responses to different task designs.

The Cluster 3 represented the players with lower distances covered and body impacts

across all zones per training. Consequently, these players spent more time below 75%

HRmax. This is the most frequent profile (47.7% of sample size), including a high

percentage of U15 and U19 players, probably because of the players’ fitness, maturity

and status level. It was suggested that higher expertise, positioning and deciding skills

(Kannekens, Elferink-Gemser, & Visscher, 2011) might result in lower physical and

physiological intensity for U19 players. In fact, high-level U19 coaches usually focus

their attention on the team strategic plans and collective tactical responses, by

improving players’ positioning. The U15 training sessions have a different perspective,

mainly focused on acquiring basic collective tactical principles such as the interpersonal

player relations in sub-phases (Duarte et al., 2012). Consequently, the frequent presence

of U15 players in cluster 3 may be the result of lower conditioning variables, such as

strength, power and speed (Malina, Eisenmann, Cumming, Ribeiro, & Aroso, 2004).

The Cluster 2 has a frequent number of U17 players that is beyond the critical period of

physical maturation in an intermediate stage of tactical expertise. Also, the progressive

understanding of the game collective tactical principles potentiated by the training

process may be responsible for the intermediate physiological profile of these players.

The Cluster 1 represented the players within higher values across all variables, but with

the lower number of players. It might be suggested that these players should be

followed with increased attention because they exhibit the higher physical and

physiological potential.

When training tasks are focused on the players’ physical development, grouping players

with similar physiological profiles and fitness level may avoid significant divergent

responses and adaptations to the stimulus. Thus, coaches would have a more accurate

and effective control on the players’ response exercises, mainly during specific blocks-

periodized training (Issurin, 2010). However, optimal performance in competitions

requires not only the physiological development, but also the technical and tactical

abilities. In this sense, caution should be applied when game-like situations are

promoted due to the players’ different perceptual-cognitive expertise. Yet, further

investigations are required to explore the short and long-term effects of this clustering

method.

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Similarity in aging, anthropometric characteristics and experience years in the studied

groups, suggest that these variables are not the most important to discriminate the

performance profiles in training. The players’ unique activity profiles suggested a

specific learning effect, as identified by body impacts resulting from players’

accelerations and decelerations in sprints with changes of direction. The body impacts

seem to be powerful predictors to represent players’ performance profiles in training

sessions. As physiological variables are suggested to be important predictors to identify

talent in youth sports, using them to establish cluster classifications may provide

reference profiles to early talent identification. Also, this classification technique may

help coaches to optimize player distribution in training groups during the practice

sessions. Consequently, this approach minimizes the variability of the physiological

outcomes, allowing coaches and fitness trainers to accurately manipulate the training

exercises and have a more effective control on the players’ responses. Thus, coaches

should not hinder mixing up players with different ages and playing positions in order

to optimize their adaptations to training stimulus.

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CAPÍTULO 6

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6.1. CONCLUSÕES E APLICAÇÕES PRÁTICAS

O planeamento dos ciclos semanais de treino assume-se como um desafio para os

treinadores, em parte pela complexidade que emerge da necessidade de combinar o

treino das capacidades físicas com o aperfeiçoamento das habilidades técnico-táticas.

Por um lado, o desenvolvimento da força muscular requer sessões de treino com

intensidades específicas que induzam adaptações neuromusculares significativas. Por

outro, a procura por estímulos fisiológicos e técnico-táticos de elevada intensidade e

variabilidade faz com que os treinadores optem frequentemente por jogos reduzidos

durante todo o ciclo anual. Neste sentido, o aprofundar de conhecimento nestes dois

tópicos configuram um problema de grande interesse para o avanço do treino

desportivo.

Procurando dar resposta a este problema, a primeira parte deste trabalho foi constituída

por dois estudos centrados nos efeitos agudos de unidades de treino de força na resposta

fisiológica, percetual, ações técnico-táticas e impulsão vertical em sessões de treino de

Andebol. Verificou-se que as unidades de treino de força precedentes a sessões de treino

constituídas por jogos reduzidos induziram valores mais elevados de frequência

cardíaca e perceção subjetiva do esforço. Mesmo com um número reduzido de

jogadores (3x3), o treino de força promoveu aumentos do tempo passado em zonas

elevadas de frequência cardíaca. Assim, a colocação de uma sessão de treino de força

máxima antes de uma unidade de treino que inclua jogos reduzidos parece ser uma

estratégia eficiente para o desenvolvimento da performance aeróbia em contexto de

jogo. Apesar disso, os resultados mostram que a capacidade de salto diminuiu

imediatamente após o treino de força máxima, com uma deterioração ainda mais

significativa após os jogos reduzidos 3x3 com treino de força antecedente,

provavelmente pela fadiga aguda e diminuição da potência muscular. Como

consequência, o maior estímulo fisiológico verificado durante os jogos 3x3 pode afetar

a eficiência de algumas ações técnico-táticas, sobretudo quando existe treino de força

antecedente.

Os jogos 3x3 parecem ser os mais indicados para o aumento da frequência de ações

individuais e estabelecimento de um padrão de jogo mais imprevisível, embora as

tomadas de decisão do jogador com bola pareçam estar limitadas. Por outro lado, os

jogos 6x6 diminuíram o número de contactos individuais com a bola e aumentaram a

variabilidade do estímulo, convergindo num padrão de resposta fisiológica mais

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intermitente. Para além disso, o 6x6 aumentou o número de passes, receções e

interceções, sugerindo uma maior interação e cooperação entre jogadores. Os valores de

impulsão vertical após os jogos 6x6 foram, no geral, superiores aos verificados no

momento após o treino de força. Assim, utilizar sessões de treino de força máxima antes

de jogos 6x6 poderá aumentar a intensidade do estímulo sem prejuízo da eficiência

técnico-tática.

Para além dos efeitos da combinação de sessões de treino com múltiplos objetivos, a

caracterização dos perfis de treino nos jogos desportivos coletivos é bastante omissa na

literatura disponível. Em particular, a descrição dos perfis de performance em idades

jovens é indispensável para um planeamento adequado e que respeite as necessidades

que os jogadores apresentam nos seus diferentes estados de maturação. Mais, conhecer

os critérios utilizados pelos treinadores na organização das sessões de treino pode ajudar

a definir estratégias de planeamento que facilitem a deteção de talentos e a otimização

da resposta fisiológica aos estímulos. Neste sentido, a segunda parte do presente

trabalho focou-se na descrição de perfis físicos e fisiológicos de sessões de treino de

futebol e na otimização da carga de treino através do estabelecimento de critérios para a

classificação dos jogadores.

Observou-se que a elevada variabilidade na resposta aos estímulos foi uma

característica chave transversal a todos os escalões (sub-15, sub-17 e sub-19). Para além

disso, os perfis de carga externa variaram em função da idade. As unidades de treino

sub-15 focaram-se em jogos reduzidos dirigidos ao desenvolvimento de princípios

técnico-táticos base, o que resultou na diminuição do estímulo fisiológico. Os jogadores

sub-17 percorreram as maiores distâncias totais e em sprint, consequência de sessões de

treino principalmente constituídas por jogos reduzidos pouco constrangidos. Os

jogadores sub-19 registaram um perfil de atividade intermitente de baixa intensidade,

em parte porque os exercícios de treino eram frequentemente interrompidos para que os

treinadores pudessem ajustar o modelo tático da equipa. Na verdade, a crescente

preocupação com os aspetos táticos do jogo pode comprometer o padrão fisiológico

exigido durante as competições de elite. Caso pretendam aumentar a intensidade do

estímulo, os treinadores deverão privilegiar mais situações de jogo pouco constrangidas.

De um ponto de vista prático, os treinadores parecem estar cientes da importância do

desenvolvimento das habilidades técnicas em idades mais jovens. À medida que a idade

biológica avança, as situações de jogo parecem ser incluídas com mais frequência nas

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unidades de treino, emergindo perfis técnicos, táticos e físicos mais próximos do padrão

competitivo.

A organização da maior parte das competições jovens baseia-se em critérios

relacionados com a idade dos jogadores. Respeitando a linha destes modelos, muitos

clubes e treinadores optam pela distribuição dos jogadores no treino em função do seu

escalão etário. Foi sugerido um modelo de classificação alternativo a este método

tradicional, apresentando alguns preditores de performance para o estabelecimento de

grupos de treino homogéneos. No geral, os resultados demonstraram que jogadores com

idades e anos de experiência idênticos podem apresentar perfis fisiológicos divergentes.

Assim, a organização de grupos baseada em perfis físicos e fisiológicos semelhantes

pode reduzir a variabilidade da resposta fisiológica e permitir a obtenção de informação

mais precisa sobre a resposta dos jogadores aos estímulos de treino. Por esse motivo, os

treinadores não deverão recear o agrupamento de jogadores com diferentes idades, anos

de experiência e postos específicos durante as sessões de treino. Uma vez que as

variáveis fisiológicas são sugeridas como preditores importantes na identificação de

talentos, esta distribuição por grupos de performance também pode providenciar perfis

de referência para a identificação de talentos em idades jovens.

Os resultados desta tese apresentam dados com implicação direta no planeamento a

curto prazo nos jogos desportivos coletivos. Os treinadores e preparadores físicos

encontram nestes estudos informação que permite manipular, com critério, a

organização de um ciclo semanal com sessões de treino dirigidas a múltiplos objetivos.

A combinação entre o treino de força e o treino de campo sempre levantou algumas

questões, que agora parecem um pouco mais claras. Quando o objetivo passa pelo

desenvolvimento da performance aeróbia, o treino de força máxima pode ser combinado

com sessões de campo, mesmo que estas sejam de intensidade elevada. Por outro lado,

se o foco estiver dirigido para o aperfeiçoamento das habilidades técnico-táticas, as

sessões de campo deverão privilegiar formas jogadas que proporcionem padrões de

performance de maior variabilidade, como o 6x6. Neste caso, como a intensidade do

estímulo é menor, o treino de força pode ser colocado antes da sessão de campo com o

propósito de promover o aumento da intensidade sem prejuízo da performance técnico-

tática.

Adicionalmente, esta tese faculta informação prática para que os treinadores possam

selecionar as tarefas que melhor otimizam a resposta ao estímulo dos jogadores durante

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as sessões de campo. Quando os treinadores optam por tarefas dirigidas ao

desenvolvimento de princípios técnico-táticos básicos, a carga externa de treino é mais

reduzida. Por outro lado, se as situações de jogo forem privilegiadas com mais

frequência, os perfis de performance irão aproximar-se do padrão competitivo, tanto

mais quanto menores forem os constrangimentos. Complementarmente, o critério da

idade tem que ser destituído como o mais importante na organização de uma sessão de

treino. Caso contrário, jogadores com perfis de performance mais elevados poderão ter

o desenvolvimento do seu potencial motor comprometido por um estímulo que não

corresponde às suas necessidades. Assim, tanto a seleção das tarefas de treino como o

seu modelo de organização parecem interferir nos perfis de carga dos jogadores. Em

suma, esta tese disponibiliza informação prática para que o planeamento do microciclo

semanal e das respetivas unidades de treino seja mais eficiente e adequado ao

desenvolvimento da performance dos jogadores.

Figura 6.1. Representação esquemática das principais aplicações práticas (resultados do

presente trabalho).

Avaliação da performance no treino em jogos desportivos...

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