A bivariate Weibull count model for forecasting association football scores

Georgi Boshnakov, Tarak Kharrat and Ian G. McHale

International Journal of Forecasting, 2017, vol. 33, issue 2, 458-466

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.

Keywords: Betting; Calibration; Copula; Counting process; Soccer; Weibull (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (36)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:33:y:2017:i:2:p:458-466

DOI: 10.1016/j.ijforecast.2016.11.006

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