Dynamic Fuzzy Logic Models for Superior Badminton Teaching and Performance Assessment

The badminton coaching and performance evaluation depend on subjective assessments and statistical analysis. Due to the unpredictable sports conditions and badminton player metrics, a more advanced method is required. This research contributes a new T-spherical fuzzy Aczel-Alsina aggregation approach to evaluate badminton match performances. Using T-spherical fuzzy sets with Aczel-Alsina aggregation enables a thorough measurement of shot accuracy, opponent adaptation, endurance, and tactical decision-making assessment in performance evaluation. The assessment method succeeds in measuring performance uncertainties through expert assessments and sports statistics, which merge with live evaluation adaptations. The model shows its strength through experimental testing, which enables effective analysis of performance rankings among players based on different match situations. The current research adds value to data-driven badminton coaching through a solution that allows trainers, analysts, and players to enhance their performance optimization techniques.