Psychophysiological profiling of elite cricket athletes

Identifying optimal psychophysiological states and developing individualized profiles can enhance emotion regulation and reduce performance variability in cricket athletes. This study examined the relationship between psychophysiological states and performance accuracy in 36 elite fast bowlers across four experimental conditions, resulting in 144 observations. Heart rate variability (HRV) and affective states, measured via the Self-Assessment Manikin (SAM), were recorded before and after accuracy-based tasks. Self-selected sensory interventions were applied prior to each over to regulate psychophysiological arousal and evoke targeted emotional responses. A Support Vector Regression (SVR) model, incorporating direction-aware distance features and evaluated with leave-one-participant-out cross-validation, emerged as the best-performing approach (R² = 0.282). This method accounted for individual differences by rescaling RMSSD values within participants and weighting deviations from personally “optimal” psychophysiological states. SHAP (SHapley Additive exPlanations) analysis further highlighted RMSSD distance and affect-based features as primary predictors of performance. These findings underscore the importance of personalized strategies for psychophysiological regulation, suggesting that traditional one-size-fits-all approaches may overlook crucial individual nuances. Overall, the results demonstrate how precise, data-driven interventions could potentially enhance consistency and precision in high-pressure sporting environments.