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网球大满贯赛事中各轮次比赛表现的变化:在保持稳定与承担风险之间权衡

Set-to-set Performance Variation in Tennis Grand Slams: Play with Consistency and Risks.

作者信息

Cui Yixiong, Liu Haoyang, Gómez Miguel-Ángel, Liu Hongyou, Gonçalves Bruno

机构信息

AI Sports Engineering Lab, School of Sports Engineering, Beijing Sport University, Beijing, China.

Facultad de Actividad Física y del Deporte (INEF),Universidad Politécnica de Madrid, Madrid, Spain.

出版信息

J Hum Kinet. 2020 Jul 21;73:153-163. doi: 10.2478/hukin-2019-0140. eCollection 2020 Jul.

Abstract

The study analysed the set-to-set variation in performance using match statistics of 146 completed main-draw matches in Australian Open and US Open 2016-2017 men's singles. Comparisons of technical-tactical and physical performance variables were done between different sets; and the within-match coefficients of variation (CV) of these variables were contrasted between match winning and losing players. All comparisons were realized via standardized (Cohen's d) mean differences and uncertainty in the true differences was assessed using non-clinical magnitude-based inferences. Results showed that there was possibly to very likely decreases in the serve, net and running related variables (mean difference, ±90%CL: -0.16, ±0.14 to -0.45, ±0.24, small) and an increase in the return and winner related variables (0.17, ±0.24 to 0.24, ±0.14, small) in the last sets when compared to the initial sets, indicating the influence of match fatigue and the player's choice of match tactics and pacing strategy. Besides, winning players were revealed to have lower CV values in most of performance variables (-0.16, ±0.24 to -0.82, ±0.23, small to moderate) except for the second serve, winner, and physical performance variables (0.25, ±0.26 to 1.6, ±0.25, small to large), indicating that they would sacrifice the consistency to gain more aggressiveness and to dominate the match.

摘要

该研究利用2016 - 2017年澳大利亚网球公开赛和美国网球公开赛男子单打146场完整正赛的比赛数据,分析了各盘之间表现的逐盘变化。对不同盘之间的技术战术和身体表现变量进行了比较;并对比了比赛胜负球员这些变量的比赛内变异系数(CV)。所有比较均通过标准化(科恩d值)均值差异实现,并使用基于非临床量级的推断评估真实差异的不确定性。结果表明,与首盘相比,末盘的发球、网前和奔跑相关变量可能至非常可能下降(均值差异,±90%置信区间:-0.16,±0.14至-0.45,±0.24,小),接发球和制胜分相关变量增加(0.17,±0.24至0.24,±0.14,小),这表明了比赛疲劳以及球员比赛战术和节奏策略选择的影响。此外,除了二发、制胜分和身体表现变量(0.25,±0.26至1.6,±0.25,小至大)外,获胜球员在大多数表现变量中的CV值较低(-0.16,±0.24至-0.82,±0.23,小至中等),这表明他们会牺牲一致性以获得更多攻击性并主导比赛。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/26fe/7386150/8b518b3d5c50/hukin-73-153-g001.jpg

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