Every weekend myself and a couple of mates from work head over to our local sports bar, where we catch the lunch time Barclays Premier League game that day.
The afternoon always starts out the same, with great debate and the odd bet or two.
The most common friendly bet we place is the goal outcome for that game. But, here's something they don't know I have.
It's helped me with the goal outcome for the last three months, just read on to discover what it is.
What is “Poisson Distribution”?
Poisson Distribution will give you the probability of a number of independent events occurring in a fixed time frame. Meaning it will give you a percentage value of the probability that team A will score 0,1, 2 or even 3 goals against team B in a soccer game amounting to +- 90 minutes.
For example, Arsenal might have an average 1.2 goals per game. When you input this data into the Poisson Distribution formula, it shows you Arsenal’s value of 17.3% chance that Arsenal will score 0 goals, 20.5% for 1 goal and 25.2% for 3 goals.
But knowing the probability of the goal outcome is not enough, to give me more successful match outcomes, there is one thing you must consider.
First you have to calculate Attack and Defence strengths
The first step, is calculating the attacking and defensive strengths of all the teams on the log table.
This is done by using the last seasons results to determine the average number of goals scored per team, per home games and per away games.
You can calculate this by taking the total number of goals scored last season and dividing it by the number of games that were played.
Goals scored at home / Number of games
Goals scored away / Number of games
The table below is for the 2015/2016 season of the Barclays Premier league for both home and away games
Now that we have these key stats we can now work out the attacking and defensive strengths for both home and away.
To work out Attacking Strength home and away, simple follow:
Average goals scored / League average
Average goals scored / League average
For example, to work out Liverpool’s Attacking Strength at home you would take their home average goals scored of 1.74 and divide it by the league average of 1.49 giving you their home attacking strength of 1.16.
Now, this will take some time so I’ve done this for you.
Attacking and Defensive strengths for the teams
You will have to keep the following tables with you when calculating the goal expectancy.
It will make sense that Manchester City will have a higher goal expectancy against a team like Aston Villa compared to Swansea. This is because of two main factors.
Manchester City will have a higher defensive strength will be Aston villa’s
Aston Villa’s attacking strength will be less than Manchester City
These two simple factors are what create the goal expectancy theory, which can be worked out for any match.
Goal Expectancy Formula
Home Team Goal Expectancy=Home Attacking Strength x Away Defensive Strength x Average Goals Home
Away Team Goal Expectancy=Away Attacking Strength x Home Defensive Strength x Average Goals Away
How to work out Goal expectancy using ‘Poisson Distribution’
Hopefully your still with me here….
If so, let’s go.
What we need to do now is use the ‘Poisson Distribution’ formula excel kindly supply’s you with.
The ‘Poisson Distribution’ formula in excel is the following:
Poisson = (x, mean, cumulative)
X = Number of Goals
Mean = Goal Expectancy
Cumulative = Set to “FALSE” so that the formula returns a value equal to the number of goals
If you have a look in Excel your formula should look like this:
=POISSON.DIST(0,1.63, FALSE) *POISSON.DIST(0,1.1, FALSE)
This gives us a probability of a 0-0 goal expectancy of 0.06%
Now should you enjoy betting on the correct score market, then this will greatly help you when betting of the following:
Home or Away Win
Under 2.5 or Over 2.5 Goals
Both Teams to Score
As a word of warning, this formula uses historical data in order to theoretically predict a goal outcome.
So test it and use it in conjunction with your other tools in your sports betting arsenal.
Until next time,