# How to predict correct scores in soccer betting using Poisson Distribution

After match result betting (Win, lose, or draw) and goal scorer prediction, correct scores are the next popular betting market in the soccer community.

Whether you’re a seasoned punter or a once-in-a-while bettor, chances are you’ve tried your luck with correct score predictions before. But like most bettors, you probably haven’t had much luck.

We’re sorry about that. Correct scores are indeed quite tricky. And sometimes, the sportsbook site you choose can limit the number of possibilities you have.

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Secondly, below is a detailed guide on using the Poisson distribution to predict soccer scores correctly.

What is the Poisson Distribution?
The Poisson Distribution is a statistical approach for converting mean averages into a probability for variable outcomes. In other words, it’s a way of predicting outcomes based on ‘average’ values of events/items in the distribution.

How to use the Poisson Distribution to predict soccer scores
To use Poisson to predict soccer score-lines, you need one important data – the average number of goals each team is likely to score in that match. This data is the platform upon which any Poisson estimation will be based.

To get this data, you simply need to figure out each team’s “Attack Strength” and “Defense Strength”.

Calculating Attack strength
Attack strength refers to a team’s tendency to score goals.

This can be calculated as thus:
You first determine the total number of goals scored in the league (by a home team) in the previous season and then divide this number by the total number of games played.

For example, in the English Premier League in the 2015/16 season, there were 567/380 at home and 459/380 away. If you divide this, you’ll get:

• Average number of goals scored at: 1.492
• Average number of goals scored away: 1.207

To get the “ATTACK STRENGTH” for any team, you simply divide the team’s average number of goals by the league’s average.

Calculating Defense strength
Defense strength refers to a team’s tendency to concede goals.

Since the number of goals scored by a home team is the same as the number of goals conceded by the away team, we can simply obtain the average league values by inverting the figures we got before.

• Average number of goals conceded at home: 1.207
• Average number of goals conceded away from home: 1.492

Like before, ‘DEFENSE STRENGTH for any team is the ratio of the team’s average and the league’s average.

Now let’s take a hypothetical match from that season. Say, the match between Tottenham and Everton in March 2017.

How many goals will Tottenham score in that match?
Step #1: Calculate Tottenham’s Attack Strength

How do we know this? In that season, Tottenham averaged 1.842 goals per game. In 19 home games, they scored 35 goals. That’s an average scoring rate of 35/19 = 1.842.

Relatively to the league’s average number of goals scored at home (1.492), Tottenham’s attacking strength would be: 1.842/1.492 = 1.235

Step #1: Calculate Everton’s Defense Strength
In that season, Everton conceded 25 goals in 19 away games. That’s an average concession rate of 25/19 = 1.315.

Relatively to the league’s average number of goals conceded away (1.492), Everton’s defensive strength would be: 1.315/1.492 = 0.881

With these two figures (Tottenham’s attack strength and Everton’s defense strength), we can now calculate the likely number of goals Tottenham will score.

We simply multiply Tottenham’s Attack Strength by Everton’s Defence Strength and the average number of home goals in the Premier League.
1.235 x 0.881 x 1.492 = 1.623
If we repeat the same procedure to predict Everton’s likely goals expectation, we will get 0.824.

Using Poisson Distribution to get actual numbers
Based on our evaluation, our score-line prediction will be something like this 1.623:0.824. Unfortunately, no soccer match ends like that.

So, how do we get something ‘reasonable?’ That’s where Poisson comes in.

Using the Poisson formula: P(x; μ) = (e-μ) (μx) / x! we can estimate possible goal outcomes. However, to save yourself the stress, you can use any Online Poisson Distribution Calculator to do the mathematical work for you.

When we applied a random Poisson tool on the internet, here’s what we got:

As you can see, the highest probable scenario for Tottenham is that they will score one goal (32.02%). While for Everton, the highest probable situation is zero goals (43.86%).

Based on that estimation, our correct score prediction would be a 1:0 outcome.

Conclusion
You should note that the Poisson Distribution is not without limitations. Sometimes, other factors can impact the outcome of a soccer match. For example, a new coach coming in, weather, injuries, form, etc.