Clustering and competitive balance in NBA and ACB professional basketball

Abstract

Some basketball leagues are more competitive than others. The level of uncertainty in the final standings is closely related to the league's appeal. A team's effectiveness has a reciprocal relationship with the emerging and critical environment: competition. Teams are affected by their surrounding environment. The competitive model directly impacts competition which means that small changes can dramatically alter the outcome. We compared two different sports models to determine the degree of hierarchy in these competitions. We studied the results of two professional basketball leagues: 18 NBA seasons (USA) and 14 ACB seasons (Spain). We found that there are three performance levels in ACB teams (ratio 0.15 +/- 0.05 0.45 +/- 0.15 0.8 +/- 0.1). However, NBA data are less scattered and more Gaussian (peak ratio 0.5). General analysis (Shannon entropy) shows that competitive balance is not stable (mean NBA Sn = 0.9842 +/- 0.0037 mean ACB Sn = 0.9793 +/- 0.0053). More detailed study (cluster analysis) shows that there are teams in the ACB which are clearly rooted in a particular area of the competition. Most NBA teams have reached the playoffs. There is no consensus in studying competitive balance. We propose using a number of methodologies in order to determine the competitiveness of a given league. The sports model has a significant impact on levels of competitive balance. Both the ACB and the NBA have high competitive balance. The NBA has specific mechanisms to ensure high competitiveness while the ACB does not meet the absence of long-run domination requirement.