Highlights Network science methodologies were able to clearly describe and quantify the point performance of elite badminton players including self and opponent related networks. The use of bipartite networks for badminton offers a novel perspective of performance analysis accounting for context and applicability of results into practice. The use of bipartite networks was in accordance with non-linear and ecological approaches, where athletes and players are considered as organisms that base their decisions on opponents and their own actions. Bipartite networks are related to non-linear and ecological approaches where, at least, two different kinds of entities are considered. In sports, we can consider players as entities that base their decisions (actions and reactions) on opponents and their own actions. Incorporation of bipartite networks into modelling of racket sport performances may bridge the gap between the performance analysis sub-discipline and coaches for greater preparation of training sessions and competitions for enhanced success. Thus, the main aim of this study was to create badminton stroke networks (BSN), from the match activities of a player and their opponents, to describe and quantify the performance of elite Olympic badminton players. The use of a Network Science approach required the development of a series of methodologies that accounted for strokes played by all medallists within an Olympic tournament and included: (i) the construction of BSN; (ii) the one-mode projections of bipartite networks (self- and opponent- networks); (iii) the centrality of one-mode projections; and (iv) the identifiability of badminton players. The BSN identified different playing patterns for medallists with the Silver medallist categorised with the less predictable and defined style of play, the Bronze medallist exhibiting the most defined style; and the Gold medallist exhibiting the greatest predictability, but only when losing points (self-networks). The use of Network Science enabled the identification of distinctive styles of play (self- and opponent-related), based on stroke performance, during successful and unsuccessful points within an Olympic tournament. Specifically, the identifiability of each player's network and its associations with point outcome, provided a better understanding of stroke performances and individual features of world-class badminton players. The use of non-linear approaches (such as bipartite networks) to measure and visualize player's performances, accounting for the specific nature of badminton and opponents, may support coaches and players with the contextualized demands of playing patterns and their performances (i.e., winning and losing points) for future success.
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