A study on the pace of Women's Singles Badminton Matches:Based on Optimal Scaling Regression Modeling Perspective
To provide data support for the daily targeted training and competition of Chinese women's badminton singles program.Adopting the video of the top 16 28-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.
万方数据
维普
