ArticleSports (Basel, Switzerland)2024
Factors Affecting the Running Performance of Soccer Teams in the Turkish Super League.
Article in Sports (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Wearable Biosensing and Machine Learning for Data-Driven Training and Coaching Support.Biosensors · 2026Review
- Uncovering the Latent Components of Physical Performance in Professional Soccer: Evidence from the Turkish First Division.Journal of functional morphology and kinesiology · 2025Article
- The Effect of a High-Frequency Exercise Program During the Transition Period in Young Football Players.Sports (Basel, Switzerland) · 2025Article
- Temperature-Related Variations in Physical Performance During Elite Soccer Matches.Sports (Basel, Switzerland) · 2024Article
- The Relationship Between Playing Formations, Team Ranking, and Physical Performance in the Serie A Soccer League.Sports (Basel, Switzerland) · 2024Article
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Authors and funding
2 authors.
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Abstract
Performance analysis in sports is a rapidly evolving field, where academics and applied performance analysts work together to improve coaches' decision making through the use of performance indicators (PIs). This study aimed to provide a comprehensive analysis of factors affecting running performance (RP) in soccer teams, focusing on low (LI), medium (MI), and high-speed distances (HI) and the number of high-speed runs (NHI). Data were collected from 185 matches in the Turkish first division's 2021-2022 season using InStat Fitness's optical tracking technology. Four linear mixed-model analyses were conducted on the RP metrics with fixed factors, including location, team quality, opponent quality, ball possession, high-press, counterattacks, number of central defenders, and number of central forwards. The findings indicate that high-press and opponent team quality affect MI (d = 0.311, d = 0.214) and HI (d = 0.303, d = 0.207); team quality influences MI (d = 0.632); location and counterattacks impact HI (d = 0.228, d = 0.450); high-press and the number of central defenders affects NHI (d = 0.404, d = 0.319); and ball possession affects LI (d = 0.287). The number of central forwards did not influence any RP metrics. This study provides valuable insights into the factors influencing RP in soccer, highlighting the complex interactions between formations and physical, technical-tactical, and contextual variables. Understanding these dynamics can help coaches and analysts optimize team performance and strategic decision making.
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