In the previous post I discussed some Poisson-like probability distributions that offer more flexibility than the Poisson distribution. They typically have an extra parameter that controls the variance, or dispersion. The reason I looked into these distributions was of course … Continue reading →
It may be that a football team who has had a hectic period with a lot of games will, because of lack of training and restitution, perform poorer. The Wikipedia page for the FA Cup mentions Manchester United’s absence from … Continue reading →
I have often seen the weather mentioned as something that could influence football results, but I have yet to see anyone looking more into it. There are various ways in which the game could be influenced by the weather, and … Continue reading →
In regular league matches, draws are a common occurrence. Modeling and predicting draws have some complications. Elo-type ratings allows for draws by simply treating them as half-wins for each team, but it does not allow for direct calculation of draw … Continue reading →
If you want to do your own number crunching on football results you need data. There are a lot of websites out there with results and statistics, but to get the information into a convenient format can be a hassle. … Continue reading →
About a moth ago Martin Eastwood of the pena.lt/y blog put up some slides from a talk he gave about predicting football results in R. He presented in detail the independent Poisson regression model, and how to implement it. He … Continue reading →
Part 1 ended with running the optimizer function to estimate the parameters in the model: In part 1 I fitted the model to data from the 2011-12 Premier League season. Now it’s time to use the model to make a … Continue reading →
Please have a look at the improved code for this model that I have posted here. When it comes to Poisson regression models for football results, the 1997 paper Modelling Association Football Scores and Inefficiencies in the Football Betting Market … Continue reading →
Last fall I took a short introduction course in Bayesian modeling, and as part of the course we were going to analyze a data set of our own. I of course wanted to model football results. The inspiration came from … Continue reading →
Adaptive Boosting, usually referred to by the abbreviation AdaBoost, is perhaps the best general machine learning method around for classification. It is what’s called a meta-algorithm, since it relies on other algorithms to do the actual prediction. What AdaBoost does … Continue reading →