Research on betting strategies for greyhound racing and other parimutuel markets presents a complex picture, with evidence of both inefficiencies and challenges in achieving sustained profitability. Some studies have identified market inefficiencies that could, in theory, be exploited for profit (Asch & Quandt, 1987; Terrell & Farmer, 1996), yet others suggest that consistently profitable strategies are difficult to implement due to market adjustments and transaction costs (Asch et al., 1984; Asch et al., 1986). Advances in machine learning, particularly neural networks and support vector regression, have shown promise in predicting race outcomes and identifying value bets, though their effectiveness varies depending on the type of wager and data quality (Johansson & Sonstrod, 2003; Schumaker & Johnson, 2008; Schumaker, 2013).
Exotic bets such as exactas and superfectas have been found to offer higher returns in certain conditions compared to simple win bets, as they may reflect a greater degree of mispricing (Schumaker & Johnson, 2008). However, the practical application of these strategies is often constrained by factors such as the cost of acquiring and processing information, the dynamic nature of betting odds, and potential limitations in capital turnover (Terrell & Farmer, 1996). While some opportunities for profitable betting exist, particularly in less efficient bet types, achieving consistent long-term profitability remains a challenge due to the inherent unpredictability of racing markets and the competitive nature of betting pools (Ziemba, 2018).
The practical application of these strategies is often constrained by factors such as the cost of acquiring and processing information, the dynamic nature of betting odds, and potential limitations in capital turnover
Summary of: Terrell & Farmer, 1996
Anecdote
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Articles Cited
- “W. Ziemba (2018): Exotic Betting at the Racetrack, https://doi.org/10.1142/11226
- The book “”Exotic Betting at the Racetrack”” by W. Ziemba covers strategies for pricing and finding profitable exotic bets at racetracks, provides examples of actual bets made by the author, and discusses major horse racing events and the performance of notable racehorses.”
- “Robert P. Schumaker, James Johnson (2008): An Investigation of SVM Regression to Predict Longshot Greyhound Races, https://doi.org/10.58729/1941-6687.1082
- The paper investigates the use of Support Vector Regression (SVR) to predict the outcomes of Greyhound races, examining the accuracy, profitability, and impact of exotic wagers on the system’s performance.”
- “U. Johansson, C. Sonstrod (2003): Neural networks mine for gold at the greyhound racetrack, https://doi.org/10.1109/IJCNN.2003.1223680
- The authors used neural networks to predict the outcomes of greyhound races using publicly available data, and their betting strategy based on the neural network predictions was able to consistently beat the market.”
- “P. Asch, B. Malkiel, R. Quandt (1986): Market Efficiency in Racetrack Betting: Further Evidence and a Correction, https://doi.org/10.1086/296321
- The authors previously reported on simulated betting strategies based on logit analysis of racetrack betting data, and found that while they were unable to devise profitable strategies for win betting, they were able to employ profitable strategies for place and show betting.”
- “P. Asch, R. Quandt (1987): Efficiency and Profitability in Exotic Bets, https://doi.org/10.2307/2554443
- The paper examines the efficiency and profitability of exotic racetrack bets, finding the markets are not efficient but the inefficiencies are insufficient to permit consistent profits from simple betting strategies, and there is some evidence of “”smart money”” using exotic bets to avoid signaling their actions.”
- “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.”
- “Robert P. Schumaker (2013): Data Mining the Harness Track and Predicting Outcomes, https://doi.org/10.58729/1941-6679.1330
- The paper presents a study on using machine learning techniques to predict harness race outcomes and outperform established prediction methods like crowdsourcing and expert bettors.”
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.
