A bivariate Weibull count model for forecasting association football scores

Boshnakov, G; Kharrat, T; McHale, IG

Abstract

The paper presents a model for forecasting association football scores. The model uses a Weibull inter-arrival-times-based count process and a copula to produce a bivariate distribution of the numbers of goals scored by the home and away teams in a match. We test it against a variety of alternatives, including the simpler Poisson distribution-based model and an independent version of our model. The out-of-sample performance of our methodology is illustrated using, first, calibration curves, then a Kelly-type betting strategy that is applied to the pre-match win/draw/loss market and to the over–under 2.5 goals market. The new model provides an improved fit to the data relative to previous models, and results in positive returns to betting.

Citation

Boshnakov, G., Kharrat, T., & McHale, I. (2017). A bivariate Weibull count model for forecasting association football scores. International Journal of Forecasting, 33(2), 458-466. https://doi.org/10.1016/j.ijforecast.2016.11.006

• Journal Article Type: Article
• Acceptance Date: Nov 21, 2016
• Online Publication Date: Jan 30, 2017
• Publication Date: Apr 1, 2017
• Deposit Date: Jan 11, 2017
• Publicly Available Date: Jan 30, 2019
• Journal: International Journal of Forecasting
• Print ISSN: 0169-2070
• Publisher: Elsevier
• Volume: 33
• Issue: 2
• Pages: 458-466
• DOI: https://doi.org/10.1016/j.ijforecast.2016.11.006
• Publisher URL: http://dx.doi.org/10.1016/j.ijforecast.2016.11.006
• Related Public URLs: https://www.journals.elsevier.com/international-journal-of-forecasting/