A multilayer network framework for soccer analysis
Fecha
2023
Título de la revista
ISSN de la revista
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Editor
Elsevier
Resumen
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
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.
Descripción
JMB is supported by Ministerio de Ciencia e Innovación (project PID2020-113737GB-I00). This research was conducted under the Sport Sciences Network (2022): 25/UPB/22 SPAA. Sports Performance Analysis Association.
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Citación
Álvaro Novillo, Bingnan Gong, Johann H. Martínez, Ricardo Resta, Roberto López del Campo, Javier M. Buldú, A multilayer network framework for soccer analysis, Chaos, Solitons & Fractals, Volume 178, 2024, 114355, ISSN 0960-0779, https://doi.org/10.1016/j.chaos.2023.114355
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