Advancing sports performance evaluation through T spherical fuzzy FUCA MCDM approach to real time basketball analytics

The process of assessing the performance of players in real time must be supported by well-developed models of decision-making in modern sports analytics, as they are required to react to uncertainty and complex data interactions. This work presents a new t-spherical fuzzy FUCA (TSF-FUCA) multi-criteria decision-making (MCDM) system of real-time basketball playing performance evaluation. The suggested technique combines the flexibility of the T-spherical fuzzy environment and the efficiency of the computational power of the FUCA algorithm to handle the ambiguity, imprecision, and multi-source information. To illustrate the practical relevance of the suggested model, a practical case that included fifteen basketball players (alternatives), seven performance criteria, and four decision-makers was created. The standards used, including shooting accuracy, defensive efficiency, teamwork, stamina, speed in decision-making, consistency and fouls committed, are both technical and tactical in nature, as they measure player performance. The sensitivity and benchmark analyses also confirmed the soundness of the TSF-FUCA approach compared to other T-spherical fuzzy and classical MCDM techniques. The results affirm that the suggested TSF-FUCA model offers a sound and smart decision-support model of real-time basketball performance analytics. In addition to the sports applications, this model adds a new dimension to the fuzzy MCDM theory as it is a flexible tool in solving complex decision-making problems in the face of uncertainty.