Market Competition and Threshold Efficiency in the Sports Industry

Abstract

Previous studies of competitive balance (CB) have analyzed the variations in game outcomes that is the second moment of winning percentage. This article differs in two aspects. First, it analyzes market competition with respect to efficiency. Second, it analyzes efficiency distribution (in particular, the third moment of the efficiency distribution and the efficiency bound). It also suggests the efficiency bound as a new measure of market competition. By applying stochastic frontier models to a panel data set of the European football leagues (English Premier League, Spanish La Liga, Italian Serie A, and German Bundesliga), it derives important implications. First, the minimum efficiency estimates seem to reveal information relevant to market competition and additional information from the conventional CB measure. Second, differences in the shapes of the efficiency distribution curves across the four leagues imply that the four leagues faced different environments in terms of market competition.

Winning in Professional Team Sports: Historical Moments

“…For example, the analysis and testing of Rottenberg's "uncertainty of outcome hypothesis" seeks to determine the impact of competitive balance on fan demand (see the surveys in * This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2016S1A2A2912186 Fort and Quirk (1995), citing Mandelbrot (1963Mandelbrot ( , 1967) and then Fama (1963Fama ( , 1965 and Fama and Roll (1968a, 1968b, 1971 in the finance literature, tested normality against non-normal stable distributions for winning percentage, but only for MLB , NBA (1975/76-1992/93), and NFL (1930-1941. Lee, Jang, and Hwang (2015) compared the win production efficiency distributions of four European football leagues and found that symmetry of the distribution is different across leagues. Groot (2008) argues for, and applies the Poisson distribution to winning.…”

“…Fort and Quirk (), citing Mandelbrot (, ) and then Fama (, ) and Fama and Roll (, , ) in the finance literature, tested normality against non‐normal stable distributions for winning percentage, but only for MLB (1952–1985), NBA (1975/76–1992/93), and NFL (1930–1941). Lee, Jang, and Hwang () compared the win production efficiency distributions of four European football leagues and found that symmetry of the distribution is different across leagues. Groot () argues for, and applies the Poisson distribution to winning.…”