Publicação
Social network analysis in football: a systematic review of performance and tactical applications
| dc.contributor.author | Alves, Ricardo | |
| dc.contributor.author | Dias, Gonçalo Nuno Figueiredo | |
| dc.contributor.author | Nunes, Nuno André | |
| dc.contributor.author | Querido, Sérgio M. | |
| dc.contributor.author | Vaz, Vasco | |
| dc.date.accessioned | 2026-05-15T15:04:50Z | |
| dc.date.available | 2026-05-15T15:04:50Z | |
| dc.date.issued | 2025-09 | |
| dc.description.abstract | Introduction:This systematic review aims to critically examine the application of social network analysis (SNA) in football, with a focus on its contribution to evaluating team performance, tactical behavior, and player interactions. Methods: Following PRISMA guidelines, a comprehensive search was conducted across four databases (PubMed, Scopus, Web of Science, and SPORTDiscus) from January 2017 to October 2024. Results: Fifty-five peer-reviewed studies met the inclusion criteria, addressing network analysis in official men's professional football matches. Data were extracted and summarized regarding methodological quality, network metrics used, tactical context, and practical implications. Discussion: Most studies demonstrated that cohesive network structures, characterized by high density, clustering coefficients, and centrality, are associated with successful team performance. Centrality metrics were frequently used to identify key tactical players, typically central defenders and midfielders. Recent methodological advances included dynamic time-window analysis, pitch-passing networks, and spatial-temporal integration using tracking data. However, there remains an overrepresentation of elite men's football and offensive phases, with limited focus on defensive networks, youth categories, and women's football. SNA offers a powerful framework to decode the complexity of football performance, evolving from static graphs to dynamic, rolesensitive, and context-rich models. Future research should adopt longitudinal designs, multi-layer network approaches, and closer collaboration with practitioners to enhance the operational utility of network insights in coaching and performance analysis.Systematic review registration: https://osf.io/2pe3y | eng |
| dc.identifier.doi | 10.3389/fpsyg.2025.1659603 | |
| dc.identifier.issn | 1664-1078 | |
| dc.identifier.uri | http://hdl.handle.net/10400.26/63163 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Frontiers Media SA | |
| dc.relation.ispartof | Frontiers in Psychology | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | football analytics | |
| dc.subject | social network analysis | |
| dc.subject | tactical behavior | |
| dc.subject | passing networks | |
| dc.subject | performance analysis | |
| dc.subject | team sports | |
| dc.subject | network metrics | |
| dc.title | Social network analysis in football: a systematic review of performance and tactical applications | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 15 | |
| oaire.citation.startPage | 1 | |
| oaire.citation.title | Frontiers in Psychology | |
| oaire.citation.volume | 16 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Dias | |
| person.givenName | Gonçalo Nuno Figueiredo | |
| person.identifier | 1146183 | |
| person.identifier.ciencia-id | 131E-C0FA-7834 | |
| person.identifier.orcid | 0000-0002-3774-6661 | |
| person.identifier.scopus-author-id | 14324779000 | |
| relation.isAuthorOfPublication | 45754c5a-e464-4564-8bb3-befbd77e85ad | |
| relation.isAuthorOfPublication.latestForDiscovery | 45754c5a-e464-4564-8bb3-befbd77e85ad |