How does curve sprint evolve across different age-categories 
in soccer players?

Alberto Filter-Ruger; Petrus Gantois; Rafael S. Henrique; Jesús Olivares-Jabalera; Jose Robles-Rodríguez; Alfredo Santalla; Bernardo Requena; Fabio Y. Nakamura

doi:10.5114/biolsport.2022.102867

eISSN: 2083-1862
ISSN: 0860-021X

Biology of Sport

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1/2022
vol. 39

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abstract:

Original paper

How does curve sprint evolve across different age-categories in soccer players?

Alberto Filter-Ruger

^{1, 2}

,

Petrus Gantois

^{3, 4}

,

Rafael S. Henrique

^{4, 5}

,

Jesús Olivares-Jabalera

^{1, 6}

,

Jose Robles-Rodríguez

⁷

,

Alfredo Santalla

^{1, 2}

,

Bernardo Requena

¹

,

Fabio Y. Nakamura

^{1, 3, 4, 8}

FSI Sport Research Lab, Granada, Spain
Department of Sports and Computer Science, Section of Physical Education and Sports, Universidad Pablo de Olavide, Seville, Spain
Associate Graduate Program in Physical Education, Federal University of Paraiba, João Pessoa, Brazil
Núcleo de Performance Retrô, Retrô Futebol Clube Brasil, Pernambuco, Brazil
Department of Physical Education, Federal University of Pernambuco, Recife, Brazil
Sport and Health University Research Institute (iMUDS), Department of Physical and Sports Education, University of Granada, Granada, Spain
Faculty of Education, Psychology and Sport Sciences, University of Huelva, Huelva, Spain
Research Center in Sports Sciences, Health Sciences and Human Development (CIDESD), University Institute of Maia (ISMAI), Maia, Portugal

Biol Sport. 2022;39(1):53–58.

DOI: https://doi.org/10.5114/biolsport.2022.102867

Online publish date: 2021/03/01

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Research has shown that soccer players regularly execute curved sprints during matches. The purpose of this study was to determine the age-related effects on curve sprint (CS) performance to both sides, asymmetry, and association with linear sprint (LS). Eighty-four soccer players (aged 16.1 ± 1.6 categorized in U15, U17, and U20) were recruited, who performed CS and LS tests. One-way analysis of variance (ANOVA) and effect size (ES) were used to compare CS performance between age categories, and relationships between physical performance measures were calculated using Pearson’s correlation coefficient. The main findings of this study were that: 1) there were significant differences in the “good” side CS among age groups (p < 0.001; ES from moderate to large), but not in the “weak” side CS, 2) curve asymmetry was significantly higher in U20 than U15 (p < 0.05; ES large) and U17 players (p < 0.05; ES moderate), and 3) relationships between CS and LS times decreased with age (from significant and very large [p < 0.001] to non-significant and smallmoderate [p > 0.05]). This study highlights the importance of assessing and training CS in different age categories, an action that becomes less correlated with LS as age increases, with the aim of mitigating the increase in asymmetries as a result of the specialization process, focusing interventions mainly on improving the CS “weak” side.

keywords:

How does curve sprint evolve across different age-categories in soccer players?

Alberto Filter-Ruger 1, 2 , Petrus Gantois 3, 4 , Rafael S. Henrique 4, 5 , Jesús Olivares-Jabalera 1, 6 , Jose Robles-Rodríguez 7 , Alfredo Santalla 1, 2 , Bernardo Requena 1 , Fabio Y. Nakamura 1, 3, 4, 8

Acceleration, Performance, Testing, Team sports, Skill

Alberto Filter-Ruger

^{1, 2}

,

Petrus Gantois

^{3, 4}

,

Rafael S. Henrique

^{4, 5}

,

Jesús Olivares-Jabalera

^{1, 6}

,

Jose Robles-Rodríguez

⁷

,

Alfredo Santalla

^{1, 2}

,

Bernardo Requena

¹

,

Fabio Y. Nakamura

^{1, 3, 4, 8}