Information and Market Efficiency: Evidence From the Major League Baseball Betting Market

Abstract

Evaluating market response to information is difficult in traditional financial markets due to their complex pricing problem. Sports betting markets greatly simplify this process. Therefore, I use moneyline data from over 88,000 Major League Baseball (MLB) games to explore the evolution of efficiency in the MLB betting market from 1977 to 2018, analyzing the manner in which it assimilates information. By comparing forecasting accuracy across years, I find that improving precision is driving a convergence between forecasts and outcomes over time, spurred specifically by changes occurring from the late 1990s to early 2000s. This period corresponds to improvements in information quality, quantity, and accessibility in the market. I then show that information assimilation within each season, through the incorporation of current-season performance, leads to an increase in accuracy. By comparing daily opening and closing lines, I find that larger relative line movements are on average less accurate, suggesting exaggerated market reactions to new information and highlighting the importance of information processing time on efficiency. In addition, I offer suggestive evidence of informed bettor presence but am unable to fully disentangle the relationships between betting volume, better composition, and accuracy.