Some people wonder if certain sports make it easier to earn higher returns on bets, but research has mixed answers. Some studies show that certain betting markets have weaknesses, which bettors can use to their advantage. For example, during the COVID-19 pandemic, NBA betting had some inefficiencies that skilled bettors could exploit (Qureshi & Zaman, 2021). Similarly, NHL betting has been found to have profitable strategies due to market flaws (Woodland & Woodland, 2001; Luxton & Cluxton, 2023).
On the other hand, other studies argue that most sports betting markets are very efficient, meaning it is difficult to find consistent opportunities for profit (Levitt, 2004; Wilkens, 2020). A bettor’s success depends on their experience, how well they analyze information, and how they handle psychological biases like overconfidence or following the crowd (d’Astous & Di Gaspero, 2013; Cantinotti et al., 2004).
Some researchers have tried using machine learning models to predict game outcomes. These models show some promise, but their ability to be profitable over the long run remains uncertain (Carloni et al., 2021; Wilkens, 2020). Even if machine learning can identify trends, bookmakers quickly adjust their odds to reduce any advantage for bettors. In general, while it may be possible to find short-term advantages in certain sports or special conditions, making money consistently from betting is extremely difficult. This is because bookmakers are constantly adjusting to new data, and betting markets tend to become more efficient over time.
A bettor’s success depends on their experience, how well they analyze information, and how they handle psychological biases like overconfidence or following the crowd
Summary of: d’Astous & Di Gaspero 2013; cantinotti et Al 2004
Anecdote
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Articles Cited
- “A. d’Astous, Marc Di Gaspero (2013): Explaining the performance of online sports bettors, https://doi.org/10.1080/14459795.2013.826709
- The study examines the factors that influence the return-on-investment (ROI) performance of online sports bettors, based on a survey of 161 online sports bettors.”
- “M. Cantinotti, R. Ladouceur, Christian Jacques (2004): Sports betting: can gamblers beat randomness?, https://doi.org/10.1037/0893-164X.18.2.143
- The study examines whether expert hockey bettors can make better predictions and achieve greater monetary gains than chance, and finds that their perceived “”skills”” are likely cognitive distortions.”
- “K. Qureshi, Tauhid Zaman (2021): The Impact of COVID-19 on Sports Betting Markets, –
- The COVID-19 pandemic led to significant inefficiencies in the moneyline betting markets for the National Basketball Association (NBA), allowing for substantial profits by betting on underdog teams, which is hypothesized to be due to the absence of live audiences during NBA games.”
- “S. Levitt (2004): Why are Gambling Markets Organized so Differently from Financial Markets?, https://doi.org/10.1111/J.1468-0297.2004.00207.X
- The sports gambling market is structured very differently from typical financial markets, with bookmakers announcing prices and taking large positions on game outcomes, which allows them to achieve higher profits by exploiting bettor biases and being more skilled at predicting game outcomes.”
- “Charles Luxton, cluxton (2023): Testing Efficiency in NHL Betting Markets Testing Efficiency in NHL Betting Markets, –
- The authors evaluate the efficiency of the NHL betting market using a multivariate probit model to identify profitable betting opportunities, which they then test on the 2020-2021 NHL season to generate an 8.5% return on investment.”
- “L. Carloni, A. D. Angelis, Giuseppe Sansonetti, A. Micarelli (2021): A Machine Learning Approach to Football Match Result Prediction, https://doi.org/10.1007/978-3-030-78642-7_63
- This paper describes a machine learning approach to predicting football match results for sports betting applications.”
- “L. Woodland, Bill M. Woodland (2001): Market Efficiency and Profitable Wagering in the National Hockey League: Can Bettors Score on Longshots?, https://doi.org/10.2307/1061582
- The National Hockey League betting market is found to be somewhat inefficient, and simple wagering strategies can result in profitable returns, as bettors tend to overbet favorites relative to their observed chance of winning, and the market does not appear to be converging to efficiency.”
- “S. Wilkens (2020): Sports Prediction and Betting Models in the Machine Learning Age: The Case of Tennis, https://doi.org/10.2139/ssrn.3506302
- The summary of the paper by S. Wilkens (2020) is that despite applying a wide range of machine learning techniques to predict the outcomes of professional tennis matches, the average prediction accuracy could not be increased beyond 70%, and returns from applying these predictions to sports betting markets were mostly negative over the longer term, with the use of model ensembles that combine predictions from multiple approaches being the most promising approach.”
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.
