Modelling football match results and the efficiency of fixed-odds betting Corresponding au.pdf

Modelling football match results and the efficiency of fixed-odds betting John Goddard* University of Wales Swansea Ioannis Asimakopoulos University of Wales Bangor * Corresponding author Address: Department of Economics University of Wales Swansea Singleton Park Swansea SA2 8PP UK Tel: +44 (0)1792 295168 Fax: +44 (0)1792 295872 E-mail: j.a.goddard@swansea.ac.uk Key words: Sports betting, efficiency, ordered probit Abstract An ordered probit regression model estimated using 15 years’ data is used to model English league football match results. As well as past match results data, the significance of the match for end-of- season league outcomes; the involvement of the teams in cup competition; the geographical distance between the two teams’ home towns; and the average attendances of the two teams all contribute to the model’s performance. The model is used to test the weak-form efficiency of prices in the fixed- odds betting market, and betting strategies with a positive expected return are identified. 1 Modelling football match results and the efficiency of fixed-odds betting 1. Introduction The predictability of match results is the main concern of research on the efficiency of sports betting markets. The recent applied statistics literature has focussed primarily on modelling goal scoring (Dixon and Coles, 1997; Rue and Salvesen, 2000; Crowder et al., 2002). Recently some econometricians have suggested modelling match results directly (rather than indirectly through scores) using discrete choice regression models (Forrest and Simmons, 2000a,b; Koning, 2000; Kuypers, 2000; Dobson and Goddard, 2001). A focus on match results rather than scores can be justified partly on grounds of simplicity: fewer parameters are required; estimation procedures are simpler; and the resulting models lend themselves to the inclusion of a variety explanatory variables. This paper presents a regression-bas