Re-examining the bias and market inefficiency in eSports betting markets: On the application of multivariate regression model

Abstract

Favorite-longshot and reverse favorite-longshot biases have become widespread in various traditional sports betting markets in recent years. However, there is a limited number of investigations that have been conducted on the eSports betting market or the bettors that operate within it. In the present research, we have made efforts to re-examine the bias and market inefficiency in four typical eSport games: League of Legends, Counter-Strike: Global Offensive, Dota 2, and King of Glory. Due to the natural characteristics of e-sports, we analyze the reasons for the market biases from 4 aspects: commission, region, match format, and tournaments. We find that both the favorite-longshot and reverse favorite-longshot bias occur in eSports. Moreover, the distribution of these betting biases is completely different among different eSports game titles and tournaments. The results of the weighted linear regression model reveal that long match format is the important factor of long-short bias, while regional tournaments are the important factor of reverse long-short bias in League of Legends.