Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/40280
Título: Applying graphs and complex networks to football metric interpretation
Autores/as: Arriaza Ardiles, Enrique
Martín-González, J.M. 
Zuñiga, M.D.
Sánchez Flores, Javier
De Saa Guerra, Yves 
García Manso, Juan Manuel 
Clasificación UNESCO: 241118 Fisiología del movimiento
5802 Organización y planificación de la educación
Palabras clave: Betweenness centrality
Closeness centrality
Clustering
Football
Network, et al.
Fecha de publicación: 2018
Publicación seriada: Human Movement Science 
Resumen: This work presents a methodology for analysing the interactions between players in a football team, from the point of view of graph theory and complex networks. We model the complex network of passing interactions between players of a same team in 32 official matches of the Liga de Fútbol Profesional (Spain), using a passing/reception graph. This methodology allows us to understand the play structure of the team, by analysing the offensive phases of game-play. We utilise two different strategies for characterising the contribution of the players to the team: the clustering coefficient, and centrality metrics (closeness and betweenness). We show the application of this methodology by analyzing the performance of a professional Spanish team according to these metrics and the distribution of passing/reception in the field. Keeping in mind the dynamic nature of collective sports, in the future we will incorporate metrics which allows us to analyse the performance of the team also according to the circumstances of game-play and to different contextual variables such as, the utilisation of the field space, the time, and the ball, according to specific tactical situations.
URI: http://hdl.handle.net/10553/40280
ISSN: 0167-9457
DOI: 10.1016/j.humov.2017.08.022
Fuente: Human Movement Science [ISSN 0167-9457], v. 57, p. 236-243
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