Odds setters as forecasters: the case of English football

By David Forrest, John Goddard, Rob Simmons. 2005

237 citations recorded by the source corpus.

Abstract Sets of odds issued by bookmakers may be interpreted as incorporating implicit probabilistic forecasts of sporting events. Employing a sample of nearly 10 000 English football (soccer) games, we compare the effectiveness of forecasts based on published odds and forecasts made using a benchmark statistical model incorporating a large number of quantifiable variables relevant to match outcomes. The experts' views, represented by the published odds, are shown to be increasingly effective over a 5-year period. Bootstraps performed on the statistical model fail to outperform the expert judges. The trend towards odds-setters displaying greater expertise as forecasters coincided with a period during which intensifying competition is likely to have increased the financial penalties for bookmakers of imprecise odds-setting. In the context of a financially pressured environment, the main findings of this paper challenge the consensus that subjective forecasting by experts will normally be inferior to forecasts from statistical models.

Subfields: Economics and Econometrics, Nature and Landscape Conservation, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/483081ff3ffa653fb4032252c74d752b675267eb

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Citations in the corpus

Issues in Sports Forecasting (2010, background): “In contrast, Forrest et al. (2005) demonstrate that there is virtually no difference between the accuracy of the forecasts of the odds makers and those obtained from a complex statistical model.”
The 12th man?: refereeing bias in English and German soccer (2010, background): “…since the abolition of betting tax in 2001, and as the growth of Internet competition has put pressure on bookmakers’ margins, there is evidence (Forrest et al., 2005) that the betting market has moved strongly towards displaying efficiency, i.e. towards odds capturing accurately all the…”
Do Sports Fans Really Value Uncertainty of Outcome?Evidence from the English Premier League (2008, unknown): “As Forrest, Goddard, and Simmons (2005) have shown, bookmakers have a far greater incentive to forecast outcomes of soccer games as precisely as information permits than do other experts, such as journalists and media pundits.”
Using ELO ratings for match result prediction in association football (2010, methodology): “Forrest, Goddard, and Simmons (2005) used one of the models from Goddard (2005): an ordered probit model including a ‘match results’ dependent variable, covariates based on lagged match results, and other relevant information.”
Forecasting: theory and practice (2020, background): “A more direct approach is to smooth the mean square errors over the lead time (Syntetos and Boylan, 2006). Strijbosch and Moors (2005) showed that unbiased forecasts will not necessarily lead to achievement, on average, of target cycle service levels or fill rates. Wallström and Segerstedt (2010) pr”
Judgmental forecasting: A review of progress over the last 25 years (2006, unknown): “Goodwin (Eds.), Forecasting with judgment (pp. 139–167). Chichester7 John Wiley & Sons. Önkal-Atay, D., Thomson, M. E., & Pollock, A. C. (2002). Judgmental forecasting.”
Predicting Wimbledon 2005 tennis results by mere player name recognition (2007, unknown): “Similar results were also reported by Forrest, Goddard, and Simmons (2005), who showed that by the end of the soccer season, odds setters' forecasts were superior to tipsters', as well as to those of sophisticated statistical benchmark models.”