I'm going to christen this effort Project Monaco. It's about Monte Carlo and Football, so it's a no brainer, right?
I'll explain the basics of the analysis...
Consider two football teams, facing each other. The result is based on a few things. How good is the home team at attacking? Conversely, how good is the away team at defending? These two things will help determine an average rate of goal scoring for the home team. There is another factor in there - the home team advantage. Some teams perform better at home than away. Others do not, and some teams even do a little better away from home (home fans can be off-putting if they're not getting behind the team). On the flip side, how good is the away side at attacking, and how well can the home team defend.
In my method, I put these numbers into a pot, and work out an average expected rate of goal scoring for each team, in the context of them playing each other. I then create a computer model of the fixture, and run about ten thousand trial games, recording the result of each. What I get is a comprehensive odds forecast, covering every score permutation.
The computer model uses a classic statistical method to model the results of each trial game. The binomial distribution. Its hard to argue with the basics of this. The one hard part we are left with is establishing the input data for the match, regarding the strengths and weakenesses of each team. The truth is, we can't be certain about them, and that leads to some complications. What we need to do is consider a range of possibilities regarding this input data, which makes things a little mroe complicated. I will explain how we work out these inputs based on the league results in the next post!
No comments:
Post a Comment