Abrar Hussain
College-level sports involve competitive athletic programs organized by universities and colleges, encompassing various disciplines. These programs require strategic decision-making at multiple levels, including athlete recruitment and financial management. Coaches, athletic directors, and sports analysts use data-driven approaches, performance metrics, and multi-criteria decision-making (MCDM) techniques to optimize team performance and resource allocation. To achieve the goal of this manuscript, we apply a broader framework of T-spherical fuzzy set (T-SFS) to manage the uncertainty of the expert’s opinion during the aggregation process. To overcome the impact of redundant and incomplete information on decision-makers, we established a decision algorithm of the CoCOSo method for resolving real-life applications and numerical examples using mathematical aggregation operators. To check the superiority of the discussed decision-making technique and fuzzy framework, we gave an experimental case study to evaluate a chosen expert for football ground using different criteria or key components. The sensitivity analysis is also conducted to showcase the consistency and reliability of diagnosed mathematical terminologies.