羽球單打比賽技術多元診斷分析

研究目的在於診斷分析羽球運動員的比賽技術。以羽球甲組單打A運動員在2013及2014年度的八場比賽為研究對象。研究方法利用多層面 Rasch模式，設定運動員（B）、評分者（R）和技術（S）三個層面，估計程式因應雙方（主、客隊）的對抗模式，程式中的指令：Model=?, -?, ?, #, R, 0.5。觀察分數的基本模式為：log(P_mnÿk/P_mnÿ)=B_m-B_n-R_i-S_j-aF_k。利用估計的非期望反應、偏差報告診斷比賽技術。結果發現：1＞透過非期望反應能收集運動員的失常或優異表現。2＞偏差報告能夠診斷運動員技術的觀察分數與期望分數差距、比較技術潛能、技術間的配對比較、運動員間的技術比較。結論：利用多層面Rasch模式能夠多元診斷運動員的比賽技術。

關鍵字

多層面Rasch模式；非期望反應；偏差報告

並列摘要

The purpose of the study was analyzing the competition of badminton athlete. Take the athlete who played eight singles between 2013 to 2014 as the object. The study method used Many-Facet Rasch Model to set the three facets, athletes (B), raters(R) and skills(S). The calculated program was based on resistance model of both sides (the host and road team). The program instruction is Model=?, -?, ?, #, R, 0.5 The basic model of score observing is log(P_mnÿk/P_mnÿ)=B_m-B_n-R_i-S_j-aF_k. Using the estimated Unexpected Responses and Bias Report to diagnose the match skills. The results were as the following. 1＞ The Unexpected Responses was able to collect the excellent and abnormal performance of athletes. 2＞ The Bias Report was able to diagnose athletes' skills such as the observation score, the expected scores difference, comparison of skill potential, the skills pairwise and comparison and the skills comparison between athletes. As the result, using Many-Facet Rasch Model is able to Multi-diagnostic athletes' skill.