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作 者:储荣芳 刘学 张晓丹[3] 金军花 CHU Rongfang;LIU Xue;ZHANG Xiaodan(Shanghai Food Science And Technology School,Shanghai,201599,China;School of Physical Education,Tianjin University of Sport,Tianjin,301617,China;School of Sports Training,Tianjin University of Sport,Tianjin,301617,China)
机构地区:[1]上海食品科技学校,上海201599 [2]天津体育学院体育教育学院,天津301617 [3]天津体育学院运动训练学院,天津301617
出 处:《四川体育科学》2024年第5期69-76,共8页Sichuan Sports Science
基 金:国家社会科学后期资助项目(20FTYB001)。
摘 要:为中国羽毛球女子单打项目的日常针对性训练及比赛提供数据支撑。采用2020年东京奥运会羽毛球女子单打项目16强28局比赛录像为切入点,使用最优尺度回归分析构建比赛节奏模型,并对2022年世界羽毛球锦标赛决赛进行案例分析。结果显示:(1)以比赛节奏为因变量,18项技术因素为自变量构建最优尺度回归模型,模型拟合度良好(R2=0.900,P<0.05)。(2)比赛节奏与个人局比赛节奏Y的关系为慢节奏(Y≥8.24)、中等节奏(6.92≤Y<8.24)、快节奏(Y<6.92),陈雨菲VS山口茜的3局中有2局的Y值高于对手。结论:(1)不同比赛节奏分别与不同技术的使用率、得分率、失误率有关联性。(2)个人比赛节奏比对手快,更易提高获胜概率。To provide data support for the daily targeted training and competition of Chinese women's badminton singles program.Adopting the video of the top 1628-game matches of women's badminton singles event of 2020 Tokyo Olympic Games as the entry point,we constructed the rhythm of play model using optimal scale regression analysis and conducted a case study on the final match of 2022 World Badminton Championships.The results showed that(1)the optimal scale regression model was constructed with competition tempo as the dependent variable and 18 technical factors as independent variables,and the model fit was good(R2=0.900,P<0.05).(2)The relationship between competition tempo and individual set competition tempo Y was slow tempo(Y≥8.24),medium tempo(6.92≤Y<8.24),and fast tempo(Y<6.92),and the Y value of 2 out of the 3 sets of Chen Yufei vs Yamaguchi was higher than that of her opponent.Conclusion:(1)Different competition tempo are correlated with the utilization rate,scoring rate,and error rate of different techniques,respectively.(2)Individuals with a faster competition tempo than their opponents are more likely to increase the probability of winning.
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