西班牙联赛中篮球运动员高性能档案的测定

IF 2.1 4区 教育学 Q1 Health Professions
Iker Madinabeitia, Bernardo Pérez, M. Gómez-Ruano, D. Cárdenas
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引用次数: 0

摘要

摘要:教练和体育科学家正在寻找一种方法来预测篮球等复杂团队运动的表现。然而,关于赢得比赛需要什么类型的球员档案,文献中没有太多信息。因此,我们的研究有两个目的:(i)通过聚类分析,确定个人游戏相关统计数据如何区分不同玩家位置之间的输赢;(ii)制定预测模型,通过决策树分析来解释更好的性能。分析了2018/2019赛季西班牙男子联赛的335场比赛,共有7345场个人统计表现。聚类分析确定了3个表现组,分别由贡献率低(FLC;23.8%的得分后卫)和高(FHC;32.1%的中锋)的外国人和贡献率低的西班牙人(SLC;32.9%的得分前锋)组成。决策树分析表明,拥有SLC和FHC档案的选手可以预测比赛中更好的结果。教练可以应用这些配置文件来构建团队组成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination of basketball players’ high-performance profiles in the Spanish League
ABSTRACT Coaches and sports scientists are looking for a way to predict performance in complex team sports such as basketball. However, concerning knowing what type of player’s profile is needed to win the competition, there is not too much information in the literature. Hence, our study had two aims: (i) to identify how the individual game-related statistics discriminate between winning and losing among different player positions through a cluster analysis; (ii) to elaborate predictive models that explain better performance through a decision tree analysis. 335 matches of the men’s Spanish League 2018/2019 were analysed, with a total of 7,345 individual statistics performances. The cluster analysis identified 3 performance groups formed by foreigners with both low (FLC; 23.8% shooting-guards) and high contributions (FHC; 32.1% centres) and Spanish with low contribution (SLC; 32.9% shooting-forwards). The decision tree analysis revealed that having players of SLC and FHC profiles predicts better results in the competition. Coaches can apply these profiles to build team composition.
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来源期刊
CiteScore
4.70
自引率
4.80%
发文量
38
审稿时长
>12 weeks
期刊介绍: The International Journal of Performance Analysis in Sport aims to present current original research into sports performance. In so doing, the journal contributes to our general knowledge of sports performance making findings available to a wide audience of academics and practitioners.
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