Predicting Football Using R

Martin Eastwood

£1Billion!bet on 2014 World Cup in UK

According to http://www.theguardian.com/sport/2014/jun/02/cashing-in-world-cup-profit-brazil

70%!of all sports betting world wide !is football

According to http://www.bbc.co.uk/sport/0/football/24354124

Not !everybody !loses to the bookmaker

The odds often reflect the!market rather than the true!probability

According to http://www.bbc.co.uk/sport/0/football/24354124

Load The Data Into R

Average Goals Scored

Average Goals Conceded

Home Advantage

Goal Distribution

Goal Distribution

Creating The Model

!

Xi,j ~ Poisson(ɑiβjƔ)!!

Yi,j ~ Poisson(ɑjβi)

Munge The Data

Fit The Model

Predicting Fixtures

Calculate Probability !Per Goal

Calculate Probability !Of Scores

Win / Loss / Draw

Over / Under

How well does it work?

Poor Accuracy For Low Scores

Poisson model assumes scores are independent of each other!!

Doesn’t account for teams motivation - e.g. playing for a draw

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

Man City Vs Man Utd

Man City = 1.88 (53%)&Draw = 4.13 (24%)&Away = 4.45 (23%)

ConclusionsPoisson 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

Questions?