Identify team sport team signature through passing network
Résumé
The traditional way of analyzing team sport performance has limitations in terms of understanding the interactions between players and the performance context. Therefore, it has been proposed to analyze teams through the lens of complexity science paradigm and to use graph theory to analyze interaction networks between players in order to assess the collective behavior. In this study, we aim at (1) investigating how a defensive imbalance constraint the emergence of interactions patterns between players and (2) identifying “team’s signature” defined as their preferences in this emergence. 24 rugby teams and 18 basketball teams of 3 young elite players played a small-sided game in 2 situations characterized by different levels of defensive imbalance (high/low). We established a list of all possible network structures (“graphlets”) and associated each possession with a graphlet to design a “profile” as the frequency of each graphlet. We evaluated the effect of the manipulated constraint on the collective behavior by comparing the mean profile of both situations, and we detected teams’ signature by clustering teams’ profiles. Results suggest that the defensive imbalance constraints more basketball teams than rugby teams, whereas team preferences seem more significant in rugby. By mobilizing complexity science paradigm and graph theory to assess collective behavior, we are able to explore the effect of a given constraint on interaction between players and to identify each team's preferred patterns of interaction. It provides a more performance-contextualized and interaction-driven analytical framework which could easily be extended afterwards.
Origine : Fichiers produits par l'(les) auteur(s)
Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification
Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification