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Introduction Competitive performance in esports is shaped not only by individual skill but also by how teams collectively manage information, coordinate actions, and adapt their behaviour within dynamic game environments. In team-based games such as League of Legends (LoL), examining behavioural differences across competitive ranks can provide insights into how expertise is expressed through coordination, spatial organisation, and decision-making. This study investigated how gameplay behaviours differ across competitive ranks within a rank-based behavioural analytics framework. Methods Match data obtained through Riot Games' official API, comprising more than 52,000 ranked matches played in 2024 across patches 14.1–14.7 and spanning all competitive ranks, were analysed. Gameplay behaviours were examined across six dimensions: combat contribution, objective control, vision, communication, movement, and combat-location patterns. Results Higher-ranked teams were not necessarily more active in combat or more frequent in objective-taking. Instead, differences across ranks were observed in information management, communication, map movement, and positioning during key gameplay moments. Lower-ranked teams demonstrated less coordinated movement and less consistent positioning, suggesting differences in collective coordination and strategic decision-making across competitive levels. Discussion These findings suggest that team-level competitive expertise in League of Legends is not defined solely by increased activity or aggression, but also by effective information management, adaptive spatial behaviour, and coordinated actions. By extending esports analytics beyond individual performance measures, this study highlights the value of examining collective behavioural patterns to understand differences in competitive expertise across ranks.
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Hojaji et al. (2026) studied this question.
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