A Novel Intuitionistic Fuzzy Decision Support System Based on Extended WASPAS Method: A Case Study for the Selection of Basketball Players and Basketball Fields for Maximum Performance

The choice of basketball players and their playing field selection represents a vital decision-making (DM) process that determines team success and game results. The selection of top players requires evaluating skills, physical attributes, and team dynamics, and selecting an appropriate field demands examination of environmental elements and infrastructure. The sports industry needs advanced decision-support methodologies to optimize its selection processes because these decisions prove complex. The multi-criteria group DM (MCDM) technique allows a panel of decision-makers (DMks) to establish a methodical system to identify the best alternative among competing criteria that produce conflicting results. The extended weighted aggregated sum product assessment (WASPAS) method serves as an effective technique because it combines the weighted sum model (WSM) and weighted product model (WPM) to evaluate and rank alternatives. The research investigates how the extended WASPAS method operates within an IFS environment to boost the processes of sports industry DM. The research selects basketball players and suitable basketball fields to maximize performance through an evaluation process that includes various performance and environmental factors. The proposed model utilizes IFS capabilities to assess decision alternatives by evaluating player skills and physical attributes, team compatibility, court surface, and environmental conditions. The extended WASPAS method produces findings comparable to traditional MCGDM approaches in establishing their effectiveness. The extended WASPAS integrated with IFS improves decision reliability and accuracy when supporting basketball player selection and venue assessments.