Inherent physical and anthropometric traits of elite soccer players, influenced by nature and nurture, account for the emergence of performances across time. Purpose: The present study aimed to evaluate inter- and intraseasonal differences and the influence of playing position on training and fitness metrics in talented young soccer players. Methods: A total of 74 male players from U20 teams of a single elite club were tested both at beginning, during, and at the end of three consecutive competitive seasons. Players under went anthropometric measurement and were tested for aerobic, jumping, and sprinting performances; the GPS-derived measures of metabolic power (MP) and equivalent distance index (ED) of every athlete were analyzed. Results: Difference between teams emerged in Mognoni's test, while it did not in countermovement jump and anthropometrics. ED was different across seasons. The model selection criteria revealed that the Bosco–Vittori test achieved the best fit. BMI and countermovement jump (CMJ) increased, and fat mass decreased, during season; different intraseasonal trends for CMJ. MP was slightly greater in midfielder. Conclusion: Network approaches in modeling performance metrics in sports team could unveil original interconnections between performance factors. In addition, the authors support multiparametric longitudinal assessments and a huge database of sports data for facilitating talent identification.

Intra- and Inter-Seasonal Fitness and Training Load Variations of Elite U20 Soccer Players

Bondi D.
;
2022-01-01

Abstract

Inherent physical and anthropometric traits of elite soccer players, influenced by nature and nurture, account for the emergence of performances across time. Purpose: The present study aimed to evaluate inter- and intraseasonal differences and the influence of playing position on training and fitness metrics in talented young soccer players. Methods: A total of 74 male players from U20 teams of a single elite club were tested both at beginning, during, and at the end of three consecutive competitive seasons. Players under went anthropometric measurement and were tested for aerobic, jumping, and sprinting performances; the GPS-derived measures of metabolic power (MP) and equivalent distance index (ED) of every athlete were analyzed. Results: Difference between teams emerged in Mognoni's test, while it did not in countermovement jump and anthropometrics. ED was different across seasons. The model selection criteria revealed that the Bosco–Vittori test achieved the best fit. BMI and countermovement jump (CMJ) increased, and fat mass decreased, during season; different intraseasonal trends for CMJ. MP was slightly greater in midfielder. Conclusion: Network approaches in modeling performance metrics in sports team could unveil original interconnections between performance factors. In addition, the authors support multiparametric longitudinal assessments and a huge database of sports data for facilitating talent identification.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/782911
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