Hybrid FAHP-FTOPSIS methodology for objective football player selection and ranking.

Practical and objective player evaluation is a critical challenge in modern sports analytics, particularly in football, where selection decisions must balance multiple performance dimensions under uncertainty. This study introduces a hybrid Multi-Criteria Decision-Making (MCDM) methodology combining the Fuzzy Analytical Hierarchy Process (FAHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) to evaluate and rank football players. The methodology integrates 12 criteria across three key domains: anthropometric attributes, fitness levels, and technical skills. FAHP is employed to derive the relative weights of criteria based on expert pairwise comparisons, while FTOPSIS calculates a closeness coefficient (CC) for each player to determine their ranking. Applied to a case study involving 20 youth football players aged 13-16, the results show that Player 10 achieved the highest closeness coefficient (CC = 0.92), followed by Player 4 (CC = 0.89) and Player 16 (CC = 0.85), indicating superior overall performance. Sensitivity analysis, including variations of ± 10% in criteria weights and performance scores, demonstrated the robustness of the top-ranked players' positions, with minimal fluctuation in CC values (e.g., Player 10's CC varied between 0.92 and 0.94). The proposed method provides a transparent and data-driven framework that accommodates variability in expert judgment and uncertainty in performance data. Despite strengths in robustness and comprehensiveness, limitations include dependence on expert input and scalability for larger datasets. Future work should explore the integration of position-specific evaluation models and their application to other sports domains. The findings highlight FAHP-FTOPSIS as a viable and rigorous approach for objective, multidimensional player selection in football.