### Predicting Football Using R

1. Predicting Football Using R Martin Eastwood
2. £1Billion! bet on 2014 World Cup in UK According to http://www.theguardian.com/sport/2014/jun/02/cashing-in-world-cup-profit-brazil
3. 70%! of all sports betting world wide ! is football According to http://www.bbc.co.uk/sport/0/football/24354124
4. Not ! everybody ! loses to the bookmaker
5. The odds often reflect the! market rather than the true! probability According to http://www.bbc.co.uk/sport/0/football/24354124
6. Load The Data Into R
7. Average Goals Scored
8. Average Goals Conceded
10. Goal Distribution
11. Goal Distribution
12. Creating The Model ! Xi,j ~ Poisson(ɑiβjƔ)! ! Yi,j ~ Poisson(ɑjβi)
13. Munge The Data
14. Fit The Model
15. Predicting Fixtures
16. Calculate Probability ! Per Goal
17. Calculate Probability ! Of Scores
18. Win / Loss / Draw
19. Over / Under
20. How well does it work?
21. Poor Accuracy For Low Scores
22. Poisson model assumes scores are independent of each other! ! Doesn’t account for teams motivation - e.g. playing for a draw
23. Applying the Dixon & Coles Adjustment x=y=0: 1-λμρ& x=0, y=1: 1+λρ& x=1, y=0: 1+μρ& x=1, y=1: 1-ρ& otherwise: 1
24. Man City Vs Man Utd Man City = 1.88 (53%)& Draw = 4.13 (24%)& Away = 4.45 (23%)
25. Conclusions Poisson model with the Dixon & Coles adjustment is simple yet relatively accurate! ! ! Other parameters, such as weather, injuries, can be added to improve accuracy! ! ! Needs combining with an effective staking strategy though
26. Questions?