A multilayer network framework for soccer analysis

dc.contributor.authorNovillo, Álvaro
dc.contributor.authorGong, Bingnan
dc.contributor.authorMartínez, Johann H.
dc.contributor.authorResta, Ricardo
dc.contributor.authorCampo, Roberto López del
dc.contributor.authorBuldú, Javier M.
dc.date.accessioned2024-04-11T13:56:02Z
dc.date.available2024-04-11T13:56:02Z
dc.date.issued2023
dc.descriptionJMB 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.es
dc.description.abstractIn 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.es
dc.identifier.citationÁlvaro 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.2023.114355es
dc.identifier.doi10.1016/j.chaos.2023.114355es
dc.identifier.issn0960-0779
dc.identifier.urihttps://hdl.handle.net/10115/32225
dc.language.isoenges
dc.publisherElsevieres
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNetwork sciencees
dc.subjectSports analyticses
dc.subjectMultilayer networkses
dc.subjectEigenvector centralityes
dc.subjectSoccer passing networkses
dc.titleA multilayer network framework for soccer analysises
dc.typeinfo:eu-repo/semantics/articlees

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