In 2001 I spent many months creating an Elo rating system for professional snooker. After numerous false starts and failed attempts, I eventually settled on a method that was producing statistically reliable figures which helped me identify value bets for matches.

The problem was that, although the painstakingly produced statistics could give me a likelihood of a player winning a match, they couldn’t tell me the likely score, which limited the number of bets I could place.

The same problem is faced by soccer punters. They can use their ratings to work out that Manchester United has a 62% chance of winning a match against Arsenal, but they can’t work out the odds of a 1-1 draw.

The solution for most professional soccer punters is to use a Poisson probability distribution model, named after a French mathematician working in the early-19^{th} Century.

The best way to understand Poisson distribution is to work through an example. If you are reasonably familiar with a programme like Excel, you should find this relatively easy to do.