Predicting bookmaker odds and efficiency for UK football

Applied Economics

Volumn 40, Issue 1, 2008, Pages 99-109

  Graham, I ^a   Stott, H ^a,b  

^a Decision Technology   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GAMBLING; MODELING; PREDICTION; SPORT;

EURASIA; EUROPE; UNITED KINGDOM; WESTERN EUROPE;

EID: 37549029190     PISSN: 00036846     EISSN: 14664283     Source Type: Journal    
DOI: 10.1080/00036840701728799     Document Type: Article

References (10)

1. Clarke, SR and Norman, JM (1995) Home ground advantage of individual clubs in English soccer. The Statistician, 44, pp. 509-521.
2. Dixon, MJ and Coles, SG (1997) Modelling association football scores and inefficiencies in the football betting market. Applied Statistics, 46, pp. 265-280.
3. Dixon, MJ and Pope, PF (2004) The value of statistical forecasts in the UK association football betting market. International Journal of Forecasting, 20, pp. 697-711.
4. Forrest, D., Goddard, J. and Simmons, R. (2005) Odds-setters as forecasters: The case of English football. International Journal of Forecasting, 21, pp. 551-564.
5. Goddard, J. (2005) Regression models for forecasting goals and match results in association football. International Journal of Forecasting, 21, pp. 331-340.
6. Karlis, D. and Ntzoufras, I. (2003) Analysis of sports data by using bivariate Poisson models. Journal of the Royal Statistical Society Series D(The Statistician), 52, pp. 381-393.
7. Koning, RH (2000) Balance in competition in Dutch soccer. The Statistician, 49, pp. 419-431.
8. Levitt, SD (2004) Why are gambling markets organised so differently from financial markets?. The Economic Journal, 114, pp. 223-246.
9. Maher, MJ (1982) Modelling association football scores. Statistica Neerlandica, 36, pp. 109-118.
10. Neumann, GR and Tamura, RF (1996) Managing Competition: The Case of the National Football League