Quality of basketballs of international level sports using an intelligent decision algorithm involving multiple...

In the competitive climate of international sports, quality assessment of basketballs assumes a critical function to guarantee performance at its best. The research proposes a new intelligent decision-making method developed to measure the global quality of professional competition basketballs. To efficiently address uncertainty and imprecision present in expert judgments, we utilize circular picture fuzzy values (CPFVs), which provide a versatile framework for representing vagueness in judgment. Addressing multi-attribute decision-making (MADM) issues involving interdependent criteria, we propose aggregation operators in the framework of Aczel-Alsina (A-A) operations under a circular prioritized picture fuzzy (CPPF) setting. In particular, we introduce two novel operators the Cr-PPF Aczel-Alsina geometric (Cr-PPFAAG) and the Cr-PPF Aczel-Alsina average (Cr-PPFAAA) as generalizations of A-A t-norm and t-conorm operators for ordered fuzzy data. We analyze the mathematical properties and relationships among these operators and embed them into a MADM model. An empirical case study investigates five prominent global basketball brands on six quality features, e.g., the durability of the material, consistency of the bounce, quality of grip, and air retention. The results of the evaluation place the Brand at the highest rank with a cumulative score of, followed by Brand ranks the lowest with 0.61. Comparative evaluation verifies the superior performance of the suggested model in dealing with ambiguity and generating strong, consistent rankings compared to other methods. The study provides real-world guidance for sports associations, manufacturers, and procurement decision-makers when choosing high-quality basketballs that comply with international performance standards and enhance professional play.