ArticleScientific reports2026
Advancing sports performance evaluation through T spherical fuzzy FUCA MCDM approach to real time basketball analytics.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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