Game over? Assessing the impact of the emergence of a profitable wagering strategy in major league baseball wagering markets

ABSTRACT

Testing the impact of profitable investment strategies is often hampered by the practical difficulties of determining who knew what, and when. This study examines the impact of the publication of a profitable wagering strategy on the Major League Baseball wagering market. While standard measures of market efficiency characterized the Major League Baseball win–loss moneyline market to be efficient, previous works shows that wagering on underdogs early in the season can generate persistent profits. Though the overall efficiency of the baseball wagering market remained after publication, these profitable opportunities dissipated. Bettor behaviour is found to play varying roles across different wagering strategies; up to half of the drop in returns can be attributed to wagering market participant behaviour.

KEYWORDS:

• Wagering markets
• market efficiency
• Major League Baseball
• moneyline
• profitability

JEL CLASSIFICATION:

• D83
• L83

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Chart depicts 3-year running average return to a one-unit wager so as to visually mitigate year-to-year volatility.

² Henceforth, ‘moneyline wagering market’ and the like will refer to the win–loss moneyline wagering market.

³ Ryan, Gramm and McKinney (2012) included only the former measure – whether the game took place in the first half of April – in their original analysis. As seasons have different start dates, the latter measure more accurately captures the nature of evolving information early in the baseball season. In addition, the start of the season is from the day in which the majority of teams play their first game. For example, in 2014, the Los Angeles Dodgers and Arizona Diamondbacks played their first regular season games on March 22. The start of the regular season for the majority of teams took place on March 31, and thus the first 2 weeks of the season stretches to April 13.

⁴ Estimated return is calculated as follows:

$EstimatedReturn=\left(Avg.Und.Line\right)\ast \left(Avg.Und.Win\mathrm{\%}\right)+\left[\left(-1\right)\ast \left(1-Avg.Und.Win\mathrm{\%}\right)\right].$