Development of an innovative method for evaluating a network of collective defensive interactions in football

(Entwicklung einer innovativen Methode zur Evaluation eines Netzwerks kollektiver Defensivinteraktionen im Fußball)

Social network analysis (SNA) has been increasingly applied to performance analytics in team sports, seeking to better understand the dynamic properties of competitive interactions. Despite considerable potential to analyze individual (micro) and team (macro) behavioral patterns of play, there are important limitations that can undermine the potential applicability of SNA. One important limitation in existing research is the lack of network analyses of defensive interactions, curtailing understanding of the functionality and adaptability of teams during competitive performance. This study developed an innovative network method for assessing interactions between players in defensive phases of play in football. The networking method was evaluated using a small-sided and conditioned game (SSCG; GK+7v7+GK) of 20 min duration (two halves of 10 min each, interspersed by 5 min intervals of active recovery). The method traced interactions between groups of three players (effective defensive triangulations) as network nodes, weighted according to the number of passes performed by the attacking players. Results showed how this social network analysis method may provide researchers, coaches and performance analysts with relevant information regarding the functional properties of teams in the defensive phase of the game. For instance, coaches and performance analysts can evaluate the geometry of a team`s defense, with players engaged in effective triangular-shaped positioning, that allowed them to provide defensive cover and balance, to protect the goal and recover ball possession.
© Copyright 2025 Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology. SAGE Publications. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Spielsportarten Naturwissenschaften und Technik
Tagging:Netzwerk Mustererkennung
Veröffentlicht in:Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology
Sprache:Englisch
Veröffentlicht: 2025
Online-Zugang:https://doi.org/10.1177/17543371221141584
Jahrgang:239
Heft:3
Seiten:412-421
Dokumentenarten:Artikel
Level:hoch