Locomotor performance parameters as predictors of high-performing male soccer teams. A multiple-season study on professional soccer.

Autor: Makar P; Faculty of Physical Education, Gdańsk University of Physical Education and Sport, Gdańsk, Poland., Musa RM; Centre for Fundamental and Continuing Education, Universiti Malaysia Terengganu, Kuala Nerus, Malaysia., Silva RM; Escola Superior de Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal.; Research Center in Sports Performance, Recreation, Innovation and Technology SPRINT, Melgaço, Portugal., Muracki J; Institute of Physical Culture Sciences, Department of Physical Culture and Health, University of Szczecin, Szczecin, Poland. jaroslaw.muracki@usz.edu.pl., Trybulski R; Provita Żory Medical Center, Żory, Poland.; Medical Department, The Wojciech Korfanty Upper Silesian Academy, Katowice, Poland., Altundağ E; Sport Science Faculty, Kütahya Dumlupınar University, Kutahya, Turkey., Altaca M; Football Industries MBA, University of Liverpool, Liverpool, UK., Kuczmik W; Department and Clinic of General Surgery, Vascular Surgery, Angiology and Phlebology, Faculty of Medical Sciences in Katowice, Medical University of Silesia in Katowice, Katowice, Poland., Studnicki R; Department of Physiotherapy, Medical University of Gdańsk, Gdańsk, Poland., Akildiz Z; Department of Coaching Education, Sports Sciences Faculty, Afyon Kocatepe University, Afyonkarahisar, Turkey.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Nov 18; Vol. 14 (1), pp. 28547. Date of Electronic Publication: 2024 Nov 18.
DOI: 10.1038/s41598-024-80181-z
Abstrakt: This study aims to explore the interplay between locomotor demands and goal differentials to better understand their combined influence on overall success. Spanning three competitive seasons within the male Turkish Super League, this study analyzed all participating teams across 124 matches. Locomotor demands, including total distance (m) covered (TD), distances covered (m) at different speed thresholds (0.21-2.0 m/s; 2.01-4.0 m/s; 4.01-5.5 m/s; and 5.5-7.7 m/s), and the number of accelerations in range of 5.5-7.0 m/s (n), were quantified using an optical tracking system. Subsequently, regression models were employed to predict the total points earned by all teams over the three seasons. The logistic regression model, tailored to predict team categorization as high-points earners (HPE) or low-points earners (LPE) based on locomotor variables, exhibited a mean accuracy of 74%. Notably, total distance covered, running speed intervals between 4.4 and 5.5 m/s, and the number of accelerations in range of 5.5-7.0 m/s emerged as significant predictors of team success. Our findings highlight the pivotal role of running speed (4.01-5.5 m/s), number of accelerations, and total distance in predicting success for high-performing teams. Coaches can leverage these insights to refine training programs, thereby optimizing team performance, and fostering success in competitive environments.
Competing Interests: Declarations Competing interests The authors declare no competing interests.
(© 2024. The Author(s).)
Databáze: MEDLINE
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