Key result
Winning esports teams linked to ~12% greater heart rate synchrony determinism during gameplay versus losers.
Why the study?
Theoretical models of real-time team coordination in esports remain lacking, prompting investigation into whether team-level physiological synchrony measured via heart rate predicts competitive success.
Does team-level physiological synchrony (measured via heart rate) predict competitive success in elite first-person shooter esports?
Does team-level physiological synchrony (measured via heart rate) predict competitive success in elite first-person shooter esports?
Winning esports teams exhibit more frequent, complex, and sustained heart rate synchrony during gameplay, suggesting a state of coordinated physiological readiness.
Team HR synchrony was associated with winning in elite esports; leaves open whether coordination drives performance or reflects other factors.
Objectives: Team success in esports is typically attributed to mechanical skill and tactical execution, yet theoretical models of real-time team coordination remain lacking. This cross-sectional study examined whether team-level physiological synchrony, measured via heart rate (HR), predicts competitive success in elite first-person shooter esports. Methods: HR data sampled at 2 Hz were collected during the 2024 Peacekeeper Elite League Fall Finals. Team-level HR synchrony was quantified using multidimensional recurrence quantification analysis (MdRQA) on 5-s binned HR series. Synchrony metrics were compared between winning and losing teams during pregame and in-game phases using robust linear mixed-effects models. Results: A total of 4.73 million HR samples were analyzed, representing 98.4 h of gameplay. No significant winner–loser differences emerged pregame. During gameplay, however, winners exhibited significantly greater synchrony across multiple MdRQA dimensions. Compared with losers, winners showed higher recurrence rate (+4.18%, Cohen d = 0.71), determinism (+12.0%, d = 0.77), laminarity (+7.03%, d = 0.50), diagonal entropy (+0.95, d = 0.82), vertical entropy (+0.76, d = 0.70), average diagonal line length (+3.0 s, d = 0.67), average vertical line length (+5.3 s, d = 0.78), and maximum line lengths (+73.2 s diagonal, d = 0.52; +45.0 s vertical, d = 0.57). These effects remained significant across 5-s delay embedded models and sensitivity analyses. Conclusions: Winning teams exhibited more frequent, complex, and sustained HR synchrony during gameplay—suggesting a state of coordinated physiological readiness. These recurrence-based signatures offer a novel biobehavioral marker for training, diagnostics, and team assessment in esports.
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GU et al. (2025) studied this question. Winning esports teams showed significantly greater heart rate synchrony during gameplay with recurrence rate +4.18% and determinism +12.0% versus losers (Cohen d >0.5).
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