中心性
计算机科学
分割
关系(数据库)
排名(信息检索)
人工智能
数据挖掘
机器学习
数学
统计
作者
Álvaro Novillo,Bingnan Gong,Johann H. Martínez,Ricardo Resta,Roberto López-Del Campo,Javier M. Buldú
标识
DOI:10.1016/j.chaos.2023.114355
摘要
In this paper, we define a novel methodology for analyzing soccer matches and teams using spatial multilayer networks. Departing from a segmentation of the pitch into h×v regions, we create 2-layer networks that capture the exchange of ball possessions between teams throughout a match. To assess the significance of each node, we employed eigenvector centrality measures within the constructed multilayer network. Furthermore, we introduce three additional metrics, namely the leakage, recovery and switching factor, which quantify the possession transitions between layers. Finally, we apply our methodology to analyze the performance of Spanish soccer teams over an entire season, using the aforementioned multilayer parameters, and discuss the relation with the playing style and ranking of soccer teams.
科研通智能强力驱动
Strongly Powered by AbleSci AI