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Poisson distribution in betting is used to calculate the frequency of any occurrence in a game. In this article, you will learn how to calculate the probability of any score in football, and how to use it to calculate who is likely tź¦•o win.

Poisson distribution was developed by 19th century French mathematician . It is a probability theory that uses historical sports dataź¦“ to predict the outcome of a sports event. It measures the likelihood of how many tā™”imes an event will occur during a specific period.

This may seem complicated to someone who has no background in maths, but it is actually a fairly simple method. To put it simply in šŸŒ„terms of football betting, PoissšŸ…˜on distribution can help you predict how likely each number of goals scored is.

When bookies set their odds, it is important to know how likely any event is, based on past performance. Bookies do not simply come up with odds out of the blue. They use mathematical models. If you want to take a scientific, mathematical approach to betting, you should calculate for yourself how likely you think a specific game event, or set of events will be. That is the first step to finding value. If you have found something thašŸ…t is more likely to happen than what the bookies predict, that is what value is.

Poisson distribution in betting is particularly relevant for gašŸ»mes like football, where scoring happens on an incremental scale. It helps you determine the likelihood of each possible score.

The Poisson distribution is commonly used to calculate the likelihood of a specific score in football, as well as a win, lose or draw. You need to first calculate your leagueā€™s average goal expectancy, along with the attack strength and defence strength for both sides.

How to calculate goal expectancy

Your team's goal expectancy depends on your teamā€™s attack strength and defence strength, and as well as that of the opposite team.

In our example, we will use the data from the 2018-2019 English Premier League to calculate a hypothetical match between Manchester City and Liverpool. Manchester is the hošŸ‘me team, whšŸŒ ile Liverpool is the away team.

Poisson distribution

Before calculating these, we need to know:

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    The total home goals scored by all EPL teams

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    The total away goals scored by all EPL teams

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    The average number of home goals and away goals per match for the whole leā™šague

We need to calculate Manchester Cityā€™s:

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    Home goal average

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    Average goals allowed per home match

We need to calculate Liverpoolā€™s:

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    Away goal average

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    Average goals allowed per away match

These stats are easy to find at

Calculating Attack Strength

With these results, we can easily calculate attack strength for the home and away team. Attack Strength is the teamā€™s average number of goals, divided by the leagueā€™s Average number of goals.

Home

Manchester Cityā€™s Attack Strength: 3.00 Ć· 1.53 = 1.96

Away

Liverpoolā€™s Attack Strength: 1.78 Ć· 1.147 = 1.55

Calculating Defence Strength

Calculating Defence Strength is just as easy. Simply divide the teamā€™s average number of goals allowed by the leagueā€™s average number of goals allowed.

Manchester Cityā€™s Defence Strength: 0.63 Ć· 1.147 = 0.55

Away

Liverpoolā€™s Defence Strength: 0.63 Ć· 1.532 = 0.41

Goal expectancy

Now that we have determined each teamā€™s Attack Strength and Defence Strength, we can calculate each teamā€™s likely score.

Manchester City goal expectancy

To determine how many goals Manchester City will likely score, we need to multiply Manchester Cityā€™s Attack Strength by Liverpoolā€™s Defence Strength and the leagueā€™s average number of home goals.

That gives us:

1.96 Ɨ 0.41 Ɨ 1.532 = 1.23

Liverpool goal expectancy

To determine how many goals Liverpool will likely score, we need to multiply Liverpoolā€™s Attack Strength by Manchester Cityā€™s Defence Strength and the leagueā€™s average number of away goals.

That gives us:

1.55 Ɨ 0.55 Ɨ 1.147 = 0.997

Average goals scored in the match

Manchester City: 1.23

Liverpool: 0.997

Using the Poisson Formula to calculate the likelihood of each possible score

Now that we have each teamā€™s home and away defence and attack strengths, we can easily use them with the Poisson formula to calculate the probability of any possible outcome.

The Poisson Formula

The Poisson Formula is:

P (k events in interval) = (Ī»k e ā€“Ī») / k!

In this formula:

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    P is the probability

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    k is the number of occurrences in the interval šŸ°(number of goals)

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    Ī» is the expected number of goals

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    e is Euler's number (e = 2.71828…)

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    k! is the factorial of k

Poisson Calculator

Using this formula, you can calculate the probability for any number of goals. However, there are plenty of which will make the job simpler. To use the calculator, fill in each possible score (limit yourself from 1 to 5) separately in the top in ā€œEvent occurrencesā€, and the expected average goals score per match in the bottom, in ā€œExpected event occurrencesā€.

That gives us tź¦he following probability fź©µor Manchester City Goals:

Manchester City Goals

That gives us tšŸ’®he following probability for Liverpool City Goals:

Liverpool City Goals

Predicting the match outcome based on these probabilities

To get each possibā›„le score, simply multiply the probability of each possible score by each team by the probability of each possible score by the other team. This gives you the following distribution:

Goals

As you can see, the most likely score is 1 ā€“ 1, or 1 ā€“ 0 followed by 0 ā€“ 0 or 0 – 1. Given the defence averages of both teams, it is easy to see how these would be very likely scores.

Bookies use Poisson distribution to calculate betting odds for outcomes in various markets. You can do the same by converting your calculated probabilities into odds. The calculations are quite simple.

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    To calculate the chance of a Manchester City win, we add all the red squares from the table above: that gives us an estišŸŒŗmated šŸ˜¼chance of 0.4142, or 41.42%

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    To calculate the chance of a Liverpool win, we add all the green squares from the table above: thaā­•t gives us an estimated chance of 0.29867, or 29.87%

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    To calculate the chance of a draw, we add all the yellow squares from the table above: that gives us anÜ« estimated chance of 0.286118, or ź©²28.61%

To convert each of šŸ¬these chances iš’‰°nto odds, we use the following formula:

Odds = 1/ (probability)

That gives us the following odds:

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    Manchester City win: 1/ (0.4142) = 2.4390

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    Liverpool win: 1/ (0.29867) = 3.3333

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    Draw: 1/ (0.286118) = 3.4483

You can convert these to American or fractional odds, but decimals are easier to work with. The calculator on our page about implied probability should help you do the maths faster.

Using Poisson distribution in betting has many advantages. First of all, it helps you understand how odds are set in the first place. By adding up the likelihood of various possibilities, bookies are able to set up relatively accurate odds. You can do the same and compare your result to what the bookies are presenting. Betting lines are not only set by using these equations. Popular matches ź¦œin particular often see the odds offered (betting lines) change, as more money comes in on a particular ā™“outcome.

That is one example of how you can use Poisson distribution to beat the bookies. Comparing your own odds to the ones offered ź§…by the bookies is part of a sound betting strategy.

Poisson distribution is a mathematical formula that offers estimated probabilities, not certainties. The more data it has to rely on, the more accurate it ź©²can get. On the other hand, no squad is the same for each match of the year.

A playerā€™s injury or absence can make a huge difference in how the entire są± quad will perform. At the beginning of the season, most teams also have a different line-up than the year before. This makes setting odds using data from a previous season problematic. Still, that does not necessarily put you at a disadvantage, since the bookies also have fewer data to rely on.

As the season goes longer, it becomes easier to predict, since there is more current data available.

It is not so hard to create your own Poisson distribution calculator with Excel; in fact, you do not need to download one from aną¶£ external site.  This step-by-step guide will show you how to make your own.

1. Calculate your teamā€™s expected goals

First, calculate your teamā€™s expected goals. That is the team's average attack strength Ɨ the other teamā€™s defence strength Ɨ average goals per match. Below, wā™e calculated Manchester Cityā€™s expected goals šŸƒat 1.23.

Check out: Expected Goals Explained.

2. Create the following table in Excel:

Manchester City Expected Goals on Excel

3. Go to the square next to 0, and right click.

4. Click on formulas> Insert Function > Poisson.Dist

Poisson.Dist on Excel

5.      Fill in:

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    X = B5 (or click on the number next to 0)

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    Mean = 1.23 (Your teamā€™s expected goals)

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    Cumulative = FALSE

Cumulative Excel

6.      Move the cursor to the bottom right of C5 and use the plus cursor to drag the formula down.

Poisson

This gives you the Poisson distribution for 0 to 5 goals of the expected goal average which is 1.23. You can combine the results of your teamā€™s probabilities to get ź§‹a distribution that looks like this (the same as the above).

Poisson distribution

Hereā„± at ThePuntersPage we have a full range of football statistics that you may also like to check out ranging across all the major countries and leagues:

It can be a bit of work understanding how to calculate odds for various game outcomes. Once you understand Poisson distribution, it becomes much simpler. Luckily, our calculatoļ·½rs, as well as the Excel method explained in this article, can help you. Knowing estimated odds and comparing them to the bookies odds is a sure path to finding value in betting.

Poisson distribution uses probability to determine the odds of any score, based on both teamā€™s past performance and league averages. First, you need to calculate each teamā€™s attack and defence strength and multiply them by the league average. Next, you use the Poisson formula to determine the likelihood of any individual scąµ©ore.

One way to predict football scores is with Poisson distribution. This is a mathematical way to estimate the probability of any score. It is bšŸ‰ased on both teamā€™s past performance and league averages. Use it to calculate each teams the likelihood of each possible number of goals for aļ·ŗ team, and multiply that by the likelihood of each possible number of goals for the other team.

Goal expectancy in football uses the following formula: Attack Strength of the team Ɨ Defence Strength of the other team Ɨ the leagueā€™s Average Number of Goals.

Attack Strength is the teamā€™s average number of goals divided by the leagueā€™s Averaā™›ge number of goals for thź¦ŗat season.

Using Poisson distribution, the probability of winning a football match is the sum of the probabilities of each individual possible winning score.

To make your own odds, first calculate or estimate the likelihood of an event, then use the following formula: Odds = 1/ (probability). Compare youršŸ¼ odds to your bookie's odds to see if they offer any value.

Hi, I'm Matteo, a writer who's passionate about all things sports. The typical weekend for me revolves around being glued to all things football on TV, ruining my Fantasy Premier League team, and getting off my lazy butt for a run.

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