First of all, if you are new to the Dixon-Coles model, get familiar with the original paper written by Mark J. Dixon and Stuart G. Coles, as it appeared in Applied Statistics in 1997.
The statistical experts at AskBettor (formerly known as Betegy) developed an algorithm based on a modified Dixon & Coles model, using Neural Network functionality to predict football results.
Books on the Dixon Coles model
Analysis of Football Prediction Methods
This is a really practical handbook, written by William Brojanigo (published in 2013). It’s probably the best book to start with if you want to get involved in football prediction methods.
This relatively short (220-pages) book studies the Dixon-Coles model (full-time scores & the difference of goals) and the Dixon-Robinson model (clustering of goal times data).
Two basic models are presented for the difference of goals based on the Discrete Normal Distribution (vs. the Skellam distribution), and the authors also use self-exciting point processes, proving that the scoring rate is mostly the highest in a short period immediately after a goal.
The Best Articles on the Dixon-Coles model
Predicting Football Results With Statistical Modelling: Dixon-Coles and Time-Weighting: Part 1 – David Sheenan’s post describes two popular improvements to the standard Poisson model for football predictions, collectively known as the Dixon-Coles model.
Predicting Football Using R some great thoughts on sports betting by Late Rooms’ Data Scientist, Martin Eastwood. Check out his SlideShare presentation!
Assessing the number of goals in soccer matches – A Master’s Thesis by Rasmus B. Olesen at the Aalborg University in Denmark – This report documents the research and results made during a Master’s thesis in Machine Intelligence. The topic of the report is sports betting and the automatic assessment of the total number of goals in soccer matches. The goal of the project is to develop, examine and evaluate proposed assessors, with regards to determining if it is possible to create a probability assessor which at the minimum can match the bookmakers’ assessments on the total number of goals in soccer matches. Secondarily, it has been examined if it is possible using defined betting strategies and probability assessor to bet at bookmakers, and earn a profit.
A great series of blog posts by Norwegian statistician Opisthokonta:
i) The Dixon-Coles model for predicting football matches in R (part 1)
ii) The Dixon-Coles model for predicting football matches in R (part 2)
iii) The Dixon-Coles model for predicting football matches in R (part 3)
Check out this R package for soccer modelling http://regista.statsandsnakeoil.com
This Reddit forum thread on the Dixon-Coles model has a few great comments from fellow Dixon-Coles fans.
This forum thread on PuntersLounge titled “Let’s Explain Dixon-Coles” also deals with the Dixon-Coles model (and how to apply it to make a profit on football betting) in great detail.
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