Favourite-longshot bias explained
In gambling and economics, the favourite-longshot bias is an observed phenomenon where on average, betters tend to overvalue "longshots" and relatively undervalue favourites. That is, in a horse race where one horse is given odds of 2-to-1, and another 100-to-1, the true odds might for example be 1.5-to-1 and 300-to-1 respectively. Betting on the "longshot" is therefore a much worse proposition than betting on the favourite. In the long run, losing 5% by betting on the favourite, but losing 40% on longshots is not uncommon.
The phenomenon was first discovered by Griffith.[1] Various theories exist to explain why people willingly bet on such losing propositions, such as risk-loving behavior, risk-averse behavior[2] or simply inaccurate estimation as presented by Sobel and Raines.[3]
Methods such as the goto_conversion,[4] Power[5] and Shin[6] can be used to measure the bias by converting betting odds to true probabilities.
See also
References
- Web site: Betting on the Longshot . 7 May 2022 .
- "We discount the chances of any party at 100/1 or bigger. The reverse of tweak 1 applies here. Almost all of these probably have effectively zero chance. Why don’t we just make them a bigger price? We don’t think we’ll take much extra money, certainly not enough to compensate us for the day we get it wrong." Matthew Shadwick, Ladbrokes, 2010-02-25. See Ladbrokes Election Forecast Feb 25th 2010
- Russell S. Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor and Francis Journals, vol. 35(4), pages 371-385, January
- Convert Betting Odds to Probabilities More Accurately and Efficiently than Shin and Power Methodshttps://github.com/gotoConversion/goto_conversion
- Adjusting Bookmaker’s Odds to Allow for Overroundhttps://www.researchgate.net/publication/326510904_Adjusting_Bookmaker's_Odds_to_Allow_for_Overround
- On determining probability forecasts from betting oddshttps://www.sciencedirect.com/science/article/abs/pii/S0169207014000533?via%3Dihub
