Analysis of competitiveness in the NBA regular seasons

Abstract

Research background and hypothesis. Several attempts have been made to understand some modalities of\nsport from the point of view of complexity. Most of these studies deal with this phenomenon with regard to the\nmechanics of the game itself (in isolation). Nevertheless, some research has been conducted from the perspective\nof competition between teams. Our hypothesis was that for the study of competitiveness levels in the system of\nleague competition our analysis model (Shannon entropy), is a useful and highly sensitive tool to determine the\ndegree of global competitiveness of a league.\nResearch aim. The aim of our study was to develop a model for the analysis of competitiveness level in team\nsport competitions based on the uncertainty level that might exist for each confrontation.\nResearch methods. Degree of uncertainty or randomness of the competition was analyzed as a factor of\ncompetitiveness. It was calculated on the basis of the Shannon entropy.\nResearch results. We studied 17 NBA regular seasons, which showed a fairly steady entropic tendency. There\nwere seasons less competitive (? 0.9800) than the overall average (0.9835), and periods where the competitiveness\nremained at higher levels (range: 0.9851 to 0.9902).\nDiscussion and conclusions. A league is more competitive when it is more random. Thus, it is harder to\npredict the fi nal outcome. However, when the competition is less random, the degree of competitiveness will\ndecrease signifi cantly. The NBA is a very competitive league, there is a high degree of uncertainty of knowing\nthe fi nal result.