Human Performance Research Centre, Faculty of Health, University of Technology Sydney, Australia.
Human Performance Research Centre, Faculty of Health, University of Technology Sydney, Australia.
J Sci Med Sport. 2020 Mar;23(3):291-296. doi: 10.1016/j.jsams.2019.09.012. Epub 2019 Sep 20.
Reducing the dimensionality of commonly reported complex network characteristics obtained from Australian Football League (AFL) games to facilitate their practical use and interpretability.
Retrospective longitudinal design where individual players' interactions, determined through the distribution and receipt of kicks and handballs, during official AFL games were collected over three seasons.
A principal component analysis was used to reduce the number of characteristics related to the cooperative network analysis.
The principal component analysis derived two individual-based principal components pertaining to in- and out-degree importance and three team-based principal components related to connectedness and in- and out-degree centralisation.
This study is the first to provide a simplified, novel method for analysing complex network structures in an Australian Football context with both the team- and individual-derived metrics revealing useful information for coaches and practitioners. This may consequently guide opposition analysis, training implementation, player performance ratings and player selection.
将从澳大利亚足球联赛（AFL）比赛中获得的常用复杂网络特征的维度降低，以方便其实际应用和解释。
回顾性纵向设计，在三个赛季中收集了个体球员通过传球和接球的分布和接收来确定的互动情况。
使用主成分分析来减少与合作网络分析相关的特征数量。
主成分分析得出了两个与个体内和个体外重要性相关的基于个体的主成分，以及三个与连通性以及个体内和个体外中心化相关的基于团队的主成分。
这项研究首次提供了一种简化的、新颖的方法来分析澳大利亚足球背景下的复杂网络结构，团队和个体衍生的指标都为教练和从业者提供了有用的信息。这可能会指导对手分析、训练实施、球员表现评级和球员选择。
