Analysis of Competitiveness in the NBA Regular Seasons

Abstract

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

Keywords: complex systems, basketball, entropy, competition, randomness.