Table 1 Comparison of existing studies on sports quality in higher education using MCDM models.

Liu³⁸

Intuitionistic Fuzzy TOPSIS

Assesses teaching quality in physical education (PE) courses

Does not utilize CPyFS for improved uncertainty handling

Incorporates CPyFS for better accuracy and reliability

Luo³⁹

Circular Fermatean Fuzzy Framework

Provides a decision algorithm for PE improvement

It uses Circular Fermatean fuzzy sets but does not integrate CPyFS-TOPSIS

Proposes CPyFS-TOPSIS for enhanced decision-making

Xue⁴⁰

Picture Fuzzy MULTIMOORA

Assesses PE quality using Picture Fuzzy Sets and Muirhead Mean

Does not apply TOPSIS or CPyFS for ranking alternatives

Introduces CPyFS-TOPSIS for more effective ranking

Li and Wang⁴¹

Machine Learning

Uses AI techniques to assess teaching frequency and effectiveness

Focuses on AI-based evaluation rather than fuzzy MCDM methods

Incorporates MCDM with CPyFS for structured evaluation

Tang⁴²

Hierarchical Fuzzy Set Theory

Evaluates PE teaching quality using fuzzy rough set differentiations

Lacks a ranking mechanism like TOPSIS for comparative assessment

Combines CPyFS and TOPSIS for precise ranking and decision-making

Proposed Work

CPyFS-TOPSIS

Provides a robust and precise evaluation model

Addresses limitations of previous studies by integrating CPyFS

Offers a more accurate, uncertainty-aware assessment method