Betting market efficiency and prediction in binary choice models Annals of Operations Research
In this paper we suggest that, in fact, betting exchanges have brought about significant efficiency gains by lowering transaction costs for consumers. We test this hypothesis using matched data on UK horse racing from betting exchanges and from traditional betting media. In contrast to traditional betting media, we find that betting exchanges exhibit both weak and strong form market efficiency. Further, we find evidence that an information based model explains the well documented favourite-longshot bias more convincingly than traditional explanations based on risk preferences.
In highly liquid markets, the odds tend to settle at a fair value before kickoff, meaning most inefficiencies disappear quickly. This makes it much harder to find profitable trades unless you have a real edge. If you are an experienced bettor, the Academy explains parlay bets, where multiple selections are combined into one wager for a higher payout but with more risk. You’ll also explore futures bets, which are perfect if you want to bet on outcomes like tournament winners or season performance early on. Each section includes in-depth guides that walk you through every detail, making sure you’re fully equipped before placing bets on sports betting sites.
One of the defining characteristics of a sports match is that the outcome is uncertain when the match is started. Betting odds offered by bookmakers are a good predictor of the probability of a certain outcome in a sport match (Stekler et al. 2010; Štrumbelj 2014). An example of the latter approach would be predictions based on a betting exchange such as Betfair, where market participants can both offer bets and accept bets (see for instance Croxson and Reade 2013; Dobson and Goddard 2017).
Finally, topics like matched betting, rollover strategy, and dafabet app avoiding loss chasing prepare you for sustainable long-term success. Traders with discipline and logic can take advantage of temporary mispricing caused by this emotional behavior. For example, our own analysis flagged that english team are overrated in European competitions. You can use tools like CGMBet to track unique insights like goal minutes, early momentum, or league-specific scoring patterns. Lower-tier competitions like Romanian Liga 2, Swedish Division 1, or Portuguese Segunda have less liquidity and media coverage.
🧱 Efficient Market Doesn’t Mean Unbeatable
Under-estimation of high probability events and over-estimation of low probability evens has also been documented in non-sports contexts (see for example Kip Viscusi 1998). The extent of market efficiency induced by rational behaviour of market participants is central for economic research. Many economists have already examined sports-betting markets as a laboratory to better understand trading behaviour and efficiency of stock prices while avoiding to jointly test the hypothesis of a correct capital market model. In view of existing market distortions as taxes, switching costs of changing betting providers and limitation in competition, the results o…
- Our results confirm weak form efficiency, while rejecting semi-strong efficiency.
- You can use tools like CGMBet to track unique insights like goal minutes, early momentum, or league-specific scoring patterns.
- The data suggests that, in most cases, a sportsbook bias of only a single point from the true median is sufficient to permit a positive expected profit.
- Additional bet types like Asian handicap, draw no bet, each way, and BTTS or both teams to score help you change your approach.
- The most common adjustment is basic normalization, where the inverse odds are divided by their sum (Štrumbelj 2014).
1 Pricing methods
Elaad et al. (2020) document odds to be unbiased in general, both in terms of the favourite-longshot bias or outcome type. In some cases, implied probabilities (or measures derived from those) are used as covariates to model, for example, match attendance or television demand. It is important that such probabilities are good estimates of the actual probability of outcome. Moreover, the analysis of the informational efficiency of the sports betting market has a broader relevance. If it can be shown that the sports betting market is efficient, then it is more likely that similar markets also process information efficiently. Similar to previous research, basic normalization and Shin’s model are used to transform betting odds into winning probabilities (Clarke et al. 2017; Koning and Boot 2020; Štrumbelj 2014).
In other words, bettors overbet underdogs more than expected given their low winning frequency, while favourites are underbet given how often they win. Hence, bettors who bet systematically on underdogs receive lower returns than bettors who bet on favourites. This paper tests the efficiency of the football betting market and develops a model of the determinants of the closing spread. The empirical results suggest that the football betting market is not perfectly efficient. The evidence also suggests that, contrary to previous studies, gamblers that do bet the long shots are acting as rational individuals attempting to maximize their return for a given level of risk. Finally, at least six variables were found to be statistically significant factors in determining closing spreads in the football betting market.
This phenomenon is known as price discovery, which I explain in my post on the Wisdom of Crowds Theory. To put market efficiency to the test, we conducted a backtest on 11,848 matches from the top seven European leagues—England, Spain, Germany, Italy, France, Belgium, and Portugal—over the past few seasons. Our results confirm weak form efficiency, while rejecting semi-strong efficiency. However, in the latter case, we are able to show the existence of profitable betting opportunities only in few of the scenarios.
What Are Obscure Betting Markets?
Alternatively, Quandt (1986) explains that this bias arises since bettors are risk-loving. In other words, bettors are willing to give up some expected return in exchange for the additional risk. Additionally, Franke (2020) suggests that bettors bias odds due to misperception of the probabilities independently of the number of possible outcomes. To succeed, you need to either outsmart the market by leveraging specialist knowledge or act quickly to capitalise on slow-moving prices. Whether you choose to dive into the world of early betting opportunities or find inefficiencies in bookmaker odds, the key is to adopt a strategic approach and continually refine your methods. The winning probabilities determined from betting odds using basic normalization are referred to as scaled probabilities.
