Yin Huagen, Zhou Yanxiang, Chen Xia, Zhang Linbao, Zhang Jingshan, Yao Cong
School of Physical Education, Shangrao Normal University, Shangrao, 334001, Jiangxi, China.
Shangrao Health Vocational College, Shangrao, 334600, Jiangxi, China.
Sci Rep. 2025 Apr 6;15(1):11783. doi: 10.1038/s41598-025-92767-2.
This study aims to scientifically evaluate the competitive performance of table tennis athletes in matches, examine the reliability and practical value of the "New Four-Phase Index Statistical Method" in statistical analysis of technical and tactical indicators, and establish a new evaluation system for technical and tactical indicators. A total of 40 significant international men's table tennis matches were selected for analysis. The video analysis method was employed to calculate the scoring rates and utilization rates of the eight sub-observational indicators within the "New Four-Phase Index." Subsequently, a table tennis technical effectiveness indicator system was established. Principal component analysis (PCA) was applied in conjunction with cluster analysis (CA) to comprehensively evaluate the competitive strength of each table tennis match and to select matches with similar strengths. The technical effectiveness data of the "New Four-Phase Index" were suitable for principal component model analysis (KMO > 0.5, P < 0.01). Following the principle that eigenvalues greater than or equal to 1 should be retained in principal component analysis, four principal components were extracted, reflecting 75.343% of the original variable information. Additionally, the overall rankings derived from the principal components analysis of the 40 matches were generally consistent with the match results. However, there were instances of imbalance between the total score and the match outcome. Cluster analysis categorized the 40 matches into three comprehensive competitive strength classes: "fluctuating competitive level," "consistent competitive level," and "weaker competitive level." Variance analysis revealed statistically significant differences among these three categories (P < 0.05). The PCA-CA comprehensive analysis model provided strong validation for the empirical research of competitive performance in table tennis matches. It effectively reflects the comprehensive competitive level of athletes in each match, offering valuable guidance to coaches for understanding their athletes' competitive states and formulating appropriate match strategies.
本研究旨在科学评估乒乓球运动员在比赛中的竞技表现,检验“新四阶段指标统计法”在技战术指标统计分析中的可靠性和实用价值,并建立新的技战术指标评价体系。共选取40场重要的国际男子乒乓球比赛进行分析。采用视频分析方法计算“新四阶段指标”内8个分项观测指标的得分率和使用率。随后,建立了乒乓球技术有效性指标体系。运用主成分分析(PCA)结合聚类分析(CA),综合评价各乒乓球比赛的竞技实力,并挑选实力相近的比赛。“新四阶段指标”的技术有效性数据适合主成分模型分析(KMO>0.5,P<0.01)。按照主成分分析中应保留特征值大于或等于1的原则,提取了4个主成分,反映了75.343%的原始变量信息。此外,对40场比赛进行主成分分析得出的总体排名与比赛结果基本一致。然而,总分与比赛结果之间存在不平衡的情况。聚类分析将40场比赛分为三个综合竞技实力等级:“波动竞技水平”、“稳定竞技水平”和“较弱竞技水平”。方差分析显示这三个等级之间存在统计学显著差异(P<0.05)。PCA-CA综合分析模型为乒乓球比赛竞技表现的实证研究提供了有力验证。它有效反映了每场比赛中运动员的综合竞技水平,为教练了解运动员的竞技状态和制定合适的比赛策略提供了有价值的指导。