arXiv subjects

Quentin Bourgeais

Publications and source records attributed to Quentin Bourgeais.

3 recordsLinked to original sources

arXiv2026

A spatio-temporal graph-based model for team sports analysis

Team sports represent complex phenomena characterized by both spatial and temporal dimensions, making their analysis inherently challenging. In this study, we examine team sports as complex systems, specifically focusing on the tactical aspects influenced by external constraints. To this end, we introduce a new generic graph-based model to analyze these phenomena. Specifically, we model a team sport's attacking play as a directed path containing absolute and relative ball carrier-centered spatial information, temporal information, and semantic information. We apply our model to union rugby, aiming to validate two hypotheses regarding the impact of the pedagogy provided by the coach on the one hand, and the effect of the initial positioning of the defensive team on the other hand. Preliminary results from data collected on six-player rugby from several French clubs indicate notable effects of these constraints. The model is intended to be applied to other team sports and to validate additional hypotheses related to team coordination patterns, including upcoming applications in basketball.

cs.SI↗

arXiv2025

Temporal passing network in basketball: the effect of time pressure on the dynamics of team organization at micro and meso levels

In this study, basketball teams are conceptualized as complex adaptive systems to examine their (re)organizational processes in response the time remaining to shoot. Using temporal passing networks to model team behavior, the focus is on the dynamics of the temporal patterns of interaction between players. Several metrics grounded in social network analysis are calculated at different level to assess the dynamics of the patterns used by teams and of the individual roles within those patterns. The results reveal a 3-phase dynamic, differentiated by more or less complex and diversified patterns, and by more or less specialized or flexible roles. Additionally, time-dependent features of the different tactical playing positions are identified, some of which linked to team performance. The findings are intended to explain how basketball teams adapt their organization to cope with time pressure, offering potential insights for other type of teams facing similar constraints. Moreover, this work provides a useful framework for a multilevel understanding of how constraints shape team adaptations dynamically, making it applicable to a wide range of team settings.

cs.DM↗

arXiv2024

A Temporal Graph Model to Study the Dynamics of Collective Behavior and Performance in Team Sports: An Application to Basketball

In this study, a temporal graph model is designed to model the behavior of collective sports teams based on the networks of player interactions. The main motivation for the model is to integrate the temporal dimension into the analysis of players' passing networks in order to gain deeper insights into the dynamics of system behavior, particularly how a system exploits the degeneracy property to self-regulate. First, the temporal graph model and the entropy measures used to assess the complexity of the dynamics of the network structure are introduced and illustrated. Second, an experiment using basketball data is conducted to investigate the relationship between the complexity level and team performance. This is accomplished by examining the correlations between the entropy measures in a team's behavior and the team's final performance, as well as the link between the relative score compared to that of the opponent and the entropy in the team's behavior. Results indicate positive correlations between entropy measures and final team performance, and threshold values of relative score associated with changes in team behavior -- thereby revealing common and unique team signatures. From a complexity science perspective, the model proves useful for identifying key performance factors in team sports and for studying the effects of given constraints on the exploitation of degeneracy to organize team behavior through various network structures. Future research can easily extend the model and apply it to other types of social networks.

cs.DM↗