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


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Makar P., Musa R. M., Silva R. M., Muracki J., Trybulski R., Altundag E., ...More

SCIENTIFIC REPORTS, vol.14, no.1, 2024 (SCI-Expanded, Scopus) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 1
  • Publication Date: 2024
  • Doi Number: 10.1038/s41598-024-80181-z
  • Journal Name: SCIENTIFIC REPORTS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, Chemical Abstracts Core, MEDLINE, Veterinary Science Database, Directory of Open Access Journals
  • Open Archive Collection: AVESIS Open Access Collection
  • Anadolu University Affiliated: Yes

Abstract

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.