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.
展开▼
机译:体育表现分析是一个快速发展的领域,学者和应用表现分析师共同努力,通过使用表现指标 (PI) 来改善教练的决策。本研究旨在对影响足球队跑步表现 (RP) 的因素进行全面分析,重点关注低距离 (LI) 、中距离 (MI) 和高速距离 (HI) 以及高速跑动次数 (NHI)。数据是使用 InStat Fitness 的光学跟踪技术从土耳其甲级联赛 2021-2022 赛季的 185 场比赛中收集的。对具有固定因素的 RP 指标进行了 4 次线性混合模型分析,包括位置、球队质量、对手质量、控球率、高位逼抢、反击、中后卫人数和中锋人数。结果表明,高位逼抢和对手球队质量会影响 MI (d = 0.311, d = 0.214) 和 HI (d = 0.303, d = 0.207);团队质量影响 MI (d = 0.632);位置和反击影响 HI (d = 0.228, d = 0.450);高位逼抢和中后卫的数量会影响 NHI(d = 0.404,d = 0.319);控球影响 LI (d = 0.287)。中锋的数量不会影响任何 RP 指标。这项研究为影响足球 RP 的因素提供了有价值的见解,突出了阵型与身体、技术战术和背景变量之间的复杂相互作用。了解这些动态可以帮助教练和分析师优化团队绩效和战略决策。
展开▼