A multilayer network framework for soccer analysis

Álvaro Novillo, Bingnan Gong, Johann H. Martínez, Ricardo Resta, Roberto López del Campo and Javier M. Buldú

Chaos, Solitons & Fractals, 2024, vol. 178, issue C

Abstract: 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.

Keywords: Network science; Sports analytics; Multilayer networks; Eigenvector centrality; Soccer passing networks (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012572

DOI: 10.1016/j.chaos.2023.114355

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