The most common researched bias in odds is the favourite longshot bias. This bias indicates the existence of lower returns to bets on longshots, competitors with low winning chances, than bets on favourites (Cain et al., 2003). Most research regarding betting market efficiency find the existence of this favourite longshot bias. This bias comes forth out of favourites being relatively underbet in comparison to longshots, and because of this betting on favourites means a higher return (Thaler and Ziemba, 1988; McKinney and Owens, 2012). The results in the paper of Bruce and Johnson (2000) indicate that the favourite longshot bias is present in the bookmaker based market, however is absence in the pari-mutuel market. Based on that the conclusion can be drawn that the origin of the favourite longshot bias lie in the decision behaviour of bookmakers. This results align with the earlier work of Shin (1991), who also argued that the bias comes forward out of the supply side.
Another important bias in the sports betting markets is the sentiment bias. Avery and Chevalier (1999) were one of the first to consider this bias. They argued that losses were abnormally high when betting on teams with a lot of supports. This prediction relied on the assumption that bookmakers would worsen the odds for teams with a lot of supporters to balance their books, since followers of sport want to bet on their favourite club. Professional betters may anticipate on this, but are unlikely to wager enough to correct for this sentiment bias (Forrest and Simmons, 2008). Furthermore, Levitt (2004) as well shows that bookmakers will change their odds based on the preference of their bettors. Moreover, Kuypers (2000) made a model that also aligns with the previous described findings.
However, the model of Kuypers (2000) is based on very restrictive assumptions. The total wager is fixed and the money distributes itself according to the relative odds. In reality this is not the case; the probability a committed Feyenoord fan will bet on the arch enemy Ajax when they play against each other when a reasonable, good price is offered is very unlikely. The fan will either decide to bet on Feyenoord or not bet at all with that bookmaker (Forrest and Simmons, 2008). This different point of view challenges the prediction that more favourite teams have higher priced odds i.e. lower pay-outs.
Furthermore, Strumpf (2003) notes that most bookmakers do not seek to entirely even their books. For example, British retail bookmakers regularly report big losses or wins based on the results of the England soccer team. This indicates that they do not fully adjust their odds to correct for sentimental wagers. Even more strongly put, some bookmaker seek to lure in new clients by offering relatively good odds on teams with large supporter bases to attract a possible large new stream of future bettors and revenue (Forrest and Simmons, 2008). Nonetheless, it is arguable that the direction and magnitude of the bias is likely to differ between bookmakers, creating different kind of positions, which could create room for surebets.
Note that there appears to be some contradiction in the biases. Often the favourite team is the more popular team. This means that the team gets better odds, because they are the favourite, however get worse odds because they are more popular. It does not appear the current literature controls for this contradiction in biases. Also, this leaves room for a potential lucrative gambling strategy, by betting on favourites that are less popular. Nonetheless, going deeper into this is outside the scope of this website, since the goal is to create a successful arbitrage strategy and not a possible lucrative betting strategy based on probabilities. A visual summary of the biases is provided in the figure below.
Avery, C., & Chevalier, J. (1999). Identifying Investor Sentiment from Price Paths: The Case of Football Betting. The Journal of Business, 72(4), 493-521.
Bruce, A. C., & Johnson, J. E. (2000). Investigating the roots of the favourite–longshot bias: an analysis of decision making by supply‐and demand‐side agents in parallel betting markets. Journal of Behavioral Decision Making,13(4), 413-430.
Cain, M., Law, D., & Peel, D. (2003). The Favourite‐Longshot Bias, Bookmaker Margins and Insider Trading in a Variety of Betting Markets.Bulletin of Economic Research, 55(3), 263-273.
Forrest, D., & Simmons, R. (2008). Sentiment in the betting market on Spanish football. Applied Economics, 40(1), 119-126.
Kuypers, T. (2000). Information and efficiency: an empirical study of a fixed odds betting market. Applied Economics, 32(11), 1353-1363.
Levitt, S. (2004) Why are gambling markets organised so differently from financial markets?, Economic Journal, 114(495), 223–246.
Shin, H. S. (1991). Optimal betting odds against insider traders. The Economic Journal, 101(408), 1179-1185.
Thaler, R. H., & Ziemba, W. T. (1988). Anomalies: Parimutuel betting markets: Racetracks and lotteries. The Journal of Economic Perspectives, 2(2), 161-174.