Question: Are greyhound racing odds more or less efficient than horse racing?

Research on betting market efficiency in horse and greyhound racing has produced mixed findings, with some studies identifying inefficiencies while others suggest that markets are generally efficient. One of the most well-documented inefficiencies is the favorite-longshot bias, where longshots tend to be overbet while favorites are underbet (Gramm & Rhodes College, 2005; Asch et al., 1984). However, other studies indicate that betting markets, particularly win pools, are relatively efficient, meaning that odds closely reflect horses’ or greyhounds’ true probabilities of winning (Bird & McCrae, 1987; Swidler & Shaw, 1995).

Market efficiency is influenced by several factors, including betting volume, race class, and the cost of acquiring and processing information. Larger betting volumes tend to reduce inefficiencies by allowing more informed bettors to influence prices (Busche & Walls, 2000). Similarly, higher-class races, which attract more experienced bettors and detailed analysis, are often found to be more efficient (Johnson et al., 2010). Information costs also play a role, as bettors with access to superior data may gain an advantage over less-informed participants, contributing to observed inefficiencies (Terrell & Farmer, 1996).

Alternative probability measures, such as Shin probabilities, have been proposed as a way to improve predictive accuracy beyond individual market prices (Cain et al., 2002). These models attempt to account for potential distortions in betting markets caused by insider information or asymmetric bettor behavior. While win pools are generally considered more efficient than place and show pools, where inefficiencies tend to persist (Swidler & Shaw, 1995), there is still debate about the extent to which market imperfections can be exploited profitably. Although many studies focus primarily on horse racing, research on greyhound racing presents additional challenges for direct comparison, as differences in race structure and betting patterns may influence market efficiency differently. Ultimately, while betting markets exhibit varying degrees of efficiency, ongoing research suggests that there is room for improvement in certain areas, particularly in less-liquid pools and among bettors who rely on less sophisticated probability assessments.

Larger betting volumes tend to reduce inefficiencies by allowing more informed bettors to influence prices

Summary of: Busche & Walls, 2000

Anecdote

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Articles Cited

• “Marshall K. Gramm, Rhodes College (2005): BETTING MARKET EFFICIENCY AT PREMIERE RACETRACKS, –
  • This paper empirically analyzes the favorite-longshot bias in betting markets at the two largest U.S. racetracks, Saratoga and Del Mar, finding that while inefficiencies exist, they are reduced as betting volume increases.”
• “D. Terrell, A. Farmer (1996): Optimal Betting and Efficiency in Parimutuel Betting Markets with Information Costs, https://doi.org/10.2307/2235361
  • The paper presents a model of parimutuel betting markets that explains several empirical observations, such as market odds failing to accurately predict outcomes and longshots earning lower expected values, as consequences of the track’s takeout and the presence of informed bettors who purchase true probabilities of events.”
• “P. Asch, B. Malkiel, R. Quandt (1984): Market Efficiency in Racetrack Betting, https://doi.org/10.1086/296257
  • The paper examines the efficiency of the racetrack betting market and whether profitable betting strategies can be devised based on observed betting patterns, finding that while such strategies may exist, they may not be exploitable on a substantial scale, and that the betting market does not necessarily exhibit irrational behavior.”
• “M. Cain, David Law, D. Peel (2002): Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market, https://doi.org/10.1080/09603100110102682
  • The study found that the efficient markets hypothesis is not supported, as “”Shin probabilities”” that account for the winning probabilities of all competitors are better able to predict race outcomes and correct the favorite-longshot bias compared to individual market prices.”
• “R. Bird, M. McCrae (1987): Tests of the efficiency of racetrack betting using bookmaker odds, https://doi.org/10.1287/MNSC.33.12.1552
  • The paper evaluates the informational efficiency of the horse racing betting market using bookmaker odds, finding that the market is generally efficient but that those with access to private information can still earn positive returns.”
• “K. Busche, W. Walls (2000): DECISION COSTS AND BETTING MARKET EFFICIENCY, https://doi.org/10.1177/104346300012004006
  • The paper examines the relationship between decision costs and market efficiency in racetrack betting markets, finding that metrics of non-optimizing behavior are inversely related to the volume of betting.”
• “Johnnie E. V. Johnson, A. Bruce, Jiejun Yu (2010): The ordinal efficiency of betting markets: an exploded logit approach, https://doi.org/10.1080/00036840802314622
  • The paper examines the ordinal efficiency of betting markets using an exploded logit approach to analyze the degree to which finishing order in horse races corresponds to probabilities inherent in odds across different categories of horse races.”
• “S. Swidler, Ron Shaw (1995): Racetrack Wagering and the `Uninformed’ Bettor: A Study of Market Efficiency, https://doi.org/10.1016/1062-9769(95)90071-3
  • The paper examines the wagering behavior of “”uninformed”” bettors at a second-tier racetrack, finding evidence of an efficient win pool but also some mispricing in the place and show pools, though the economic consequences of this mispricing may be small.”

Insufficient Detail?

At times it is difficult to answer the question as there are not enough relevant published journal articles to relate. It could be that the topic is niche, there’s a significant edge (and researchers prefer not to publish), there is no edge or simply no one has thought to investigate.