The Relationship Between Individually Assessed High-Intensity Accelerations, High-Intensity Decelerations, Sprints, and Technical Performances During Soccer Matches: A Full Season Analysis.

Hugo Silva, Fábio Yuzo Nakamura, Gibson Praça, João Ribeiro, Rui Marcelino
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Abstract

Purpose: This longitudinal study analyzed the relationship between players' physical (sprint distances, number of high-intensity accelerations and decelerations assessed with individual and relative thresholds) and technical (retrieved from SofaScore platform) performances during competition. Methods: Twenty elite players were monitored across a full season. Physical performances were monitored with GNSS devices, retrieving time (s), velocity (km.h-1) and distance (m). Sprint distances were calculated as > 80% of the match peak speed registered across the season. High-intensity accelerations and decelerations were calculated as >75% of the peak values registered across the season. Pearson (r) correlations (with 95% confidence intervals) were calculated to assess the relationship among different physical performance variables and between the physical and technical performance variables. Results: Sprint distances correlated with the number of ball touches (r = -0.36 [-0.49, -0.23], p < .001), accurate passes (r = -0.45 [-0.56, -0.32], p < .001), and dribble attempts (r = 0.30 [0.16, 0.43], p < .001). If players touched the ball more frequently and pass the ball more accurately, they covered shorter sprint distances. However, if players attempted more dribbles, they covered longer sprint distances. Conclusion: Practitioners can develop tactical strategies considering the relationship between sprint distances and technical variables such as ball touches, accurate passes, and dribble attempts.

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足球比赛中个人评估的高强度加速、高强度减速、短跑和技术表现之间的关系:全赛季分析
目的:本纵向研究分析了球员在比赛中的体能(短跑距离、高强度加速和减速次数,以个人和相对阈值进行评估)和技术(从 SofaScore 平台获取)表现之间的关系。方法:对 20 名精英球员进行了整个赛季的监测。使用全球导航卫星系统(GNSS)设备监测身体表现,检索时间(秒)、速度(公里/小时-1)和距离(米)。短跑距离的计算方法是,整个赛季记录的比赛峰值速度大于 80%。高强度加速度和减速度的计算方法是:大于整个赛季记录峰值的 75%。计算了皮尔逊(r)相关性(置信区间为 95%),以评估不同体能表现变量之间以及体能和技术表现变量之间的关系。结果显示冲刺距离与触球次数相关(r = -0.36 [-0.49, -0.23],p r = -0.45 [-0.56, -0.32],p r = 0.30 [0.16, 0.43],p 结论:练习者可以考虑冲刺距离与触球、准确传球和运球尝试等技术变量之间的关系来制定战术策略。
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