A novel multiple criteria ranking approach for determining the Most Valuable Player (MVP) of a sport season: A numerical study from NBA league

Abstract

Team sports have gained a significant place in society, generating debates about team strengths, player merits, and ultimately, determining champions. The National Basketball Association (NBA) offers various individual awards, with the MVP award holding paramount importance. Selecting the MVP necessitates a comprehensive approach considering both statistical performance and team success throughout the season. This study presents a fuzzy decision-making approach to compare the performance of players and identify the MVP of the League. A case study for the 2022-2023 NBA season is presented in this study, wherein 535 players' regular season statistics are analyzed. Correlation analysis is employed to eliminate the criteria which are dependent on each other. Therefore, the number of criteria has been decreased from twenty to seven which are defined as key metrics: (i) matches won, (ii) points scored per game, (iii) shooting percentage, (iv) rebounds per game, (v) assists per game, (vi) steals per game, and (vii) blocks per game. After correlation analysis, Full Consistency Method (FUCOM) is employed to determine the importance weights of the criteria. We have employed a specific normalization procedure and employed information axiomatic design (IAD) to rank players based on their total information contents. The case study proves the feasibility and applicability of the proposed methodology for multiple criteria ranking problem. Future research may focus on position-specific rankings, providing more accurate assessments, and extending analysis to youth leagues for draft day decisions.