Testing Market Efficiency in the Major League Baseball Over-Under Betting Market

2002 ◽  
Vol 3 (4) ◽  
pp. 311-319 ◽  
Author(s):  
Kenneth H. Brown ◽  
Fred J. Abraham
Author(s):  
Rodney J. Paul ◽  
Andrew P. Weinbach

This article discusses the literature that uses sports gambling markets as an analogy to financial markets. It also expands the study of actual sportsbook behavior, comparing the traditional models to the Levitt hypothesis and considering alternative theories, by examining the betting market for Major League Baseball (MLB). The reverse favorite-longshot bias and home/road biases are then explored. It appears that bettors prefer road favorites by a large margin, but this is not captured by the sportsbook odds, which, likely not coincidentally, tend to map closer to actual favorite win percentages. There are no statistically significant returns to betting against the public. The findings that sportsbooks do not set prices to balance the book calls into question the source of some of the earlier findings of market efficiency in sports wagering markets and its underlying support for the forecasting power of prediction markets.


2013 ◽  
Vol 6 (1) ◽  
pp. 79-92
Author(s):  
Matt E Ryan ◽  
Marshall Gramm ◽  
C. Nicholas McKinney

Previous studies of the National Hockey League (NHL) betting market claim a general movement towards efficiency over the last two decades.  These studies, however, assume a homogenous betting market with regards to the time of year in which bets are placed.  Differences in available information—information effects—have been shown to distort the Major League Baseball betting market; they produce similar distortions when considered in the NHL market as well.  As such, previous claims of market efficiency must be revisited in light of heterogeneous information.


2015 ◽  
Vol 9 (2) ◽  
pp. 43-63
Author(s):  
Rodney Paul ◽  
Andrew Weinbach

The use of prediction markets is extended to explain differences in preferences of fans that purchase different price levels of tickets under dynamic pricing for Major League Baseball.  Using data from eleven teams, this research investigates similarities and differences in variables that affect ticket prices for the highest-priced and lowest-priced tickets.  Key contrasts between the groups are found to stem from distinct preferences for uncertainty of outcome, measured by betting market odds, and team quality.  It is also shown that differences between the groups are attributable to sensitivity to factors such as key opponents, weekend games, opening day, and temperature.


Author(s):  
Rodney J. Paul ◽  
Andrew P. Weinbach ◽  
Brad R. Humphreys

This study explores the impact of elite starting pitchers on the Major League Baseball betting market. Starting pitchers are the key defensive element of a baseball game, and their value is generally reflected in the market odds on baseball games. This study uses highly detailed and previously unavailable data to examine the role of elite starting pitchers on game betting volume, percentage bet on the favorite and the underdog, and percentage bet on the “over” and the “under” in the baseball totals market. Not surprisingly, games involving an elite pitcher see significant differences in betting percentages and play a key role in the determination of betting volume. In addition, the star-player nature of elite pitchers being of a defensive, rather than offensive, nature leads to bettors wagering significantly more on the under in games involving elite starting pitchers.


2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Jeremy Losak ◽  
Joseph Sabel

Home field advantage is universally accepted across most major sports and levels of competition. However, exact causes of home field advantage have been difficult to disentangle. The COVID-19 pandemic offers a unique, natural experiment to isolate elements related to home field advantage since all 2020 regular season Major League Baseball games were played without fans. Results provide no statistically significant evidence of a difference in home field advantage between the 2019 and 2020 seasons, evidence that home crowd support is not a driver of home field advantage. There does appear to be a statistical advantage by the home team batting second in the inning. Travel fatigue seems to have no impact on home field advantage, and while home field advantage seems to increase throughout the 2020 season, we chalk that up to small sample noise. Despite lacking historical precedence, betting markets seemingly respond efficiently to the new home conditions. Keywords: home field advantage, market efficiency, baseball, ghost games


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