# HOW TO DO SCIENTIFIC OR MATHEMATICAL CORRECT SCORE PREDICTION

Updated: Jan 8, 2020

In this article, I will teach you how to do scientific and mathematical __correct score predictions__. The aim is finding the correct score result with the highest probability of coming to pass given historical matches results and current form.

1. Make an artificial control of the number of goals a single team can score.

2. Use Poisson distribution to calculate the probabilities for every included goal number for individual teams

3. Apply joint probability distribution to get the probabilities for each goal combination

4. Choose the goal combined with the largest joint probability

Make an artificial control of the number of goals a single team can score.

It is mathematically self-defeating to start using the whole probability space possible in making correct score predictions. This is because the probability space would be too large forcing you to use a continuous probability distribution as opposed to a more meaningful discrete probability distribution.

Really do not want to calculate the probability of a team scoring 43 goals or 1,000,000 goals for that matter. Actually, most bookmakers only list less than 20 possible outcomes, the most likely ones. If you have never noticed, most betting firm list outcomes with total goals equal to or less than 6.

However, for perspective, I will use 12 total goals to show you how to make profitable sure correct score odds.

Now that we have set our control at 6 goals per team maximum, it is time to go to the next step.

Use Poisson distribution to calculate the probabilities for every included goal number for individual teams

Poisson distribution is the best to come up with probabilities for expected goals by each team. The only thing you need to do this is knowledge of the distribution function and the mean number of goals for each team in the last 10 or 15 matches they have played.

To be honest, with today’s technology, you do not need to know the Poisson distribution off the head or even know how to use it with a pen and paper. You can simply use a computer’s spreadsheet and you will find it there for easy calculation. I f you wish to have my excel templates for the distribution fully furnished with the whole prediction process (including the Poisson distribution function)let me know in the comment section.

In this case, we are going to use the example of __Arsenal vs Liverpool__. First, we need to get the average number of goals the two teams have scored against each other in similar matches when Arsenal was at home and Liverpool away.

Surebet core systems show that Arsenal has scored an average of 1.6 goals while at home against Liverpool in their last 13 games. Liverpool has however scored an average of 1.31 goals during those matches.

Second, you need the average number of goals for each team in similar circumstances (Arsenal at home and Liverpool away). This will include matches with all the other teams they have played.

Using this criterion, Arsenal has averaged 2.13 goals per match against all teams since 2006 while Liverpool has averaged 1.58 goals per match while away.

The third and last averages we need are the weighted averages. The reason for weighting is that team form and performance changes from time to time. It is therefore beneficial if we give more weight to recent matches as opposed to older matches.

Using this criterion we find that Arsenal’s home average weighted goals are 1.845 while Liverpool’s away weighted goals are 1.425.

Now we need 3 tables to represent Poisson probabilities for these mean averages.

Below is a Poisson distribution table for the general average goals criteria.

Below is a Poisson distribution table for the head to head average criteria.

Below is a Poisson distribution table for the time-weighted average goals criteria.

### Apply joint probability distribution to get the probabilities for each goal combination

The next step is to find joint probabilities for all the 36 possible outcomes for this game. Remember up to this point, we have treated each variable independently.

The Poisson probabilities represented are totally independent for each team. We, however, have to end the independence now and join them to get joint probabilities for the possible outcome. Note that no match can end with results for only one side.

So, for instance, we have to find the probability of Arsenal scoring 0 goals while Liverpool scores 0 goals as well.

Due to independence, we shall simply multiply the probabilities, outcomes per outcome.

For a (0:0) result, we will multiply:

P(Arsenal=0) x P(Liverpool=0)

=2.4% using the general average criteria

Or

=3.8% using the head to head criteria

Or

=5.4% using the weighted goals criteria.

Repeating the process for all possible outcomes, we get the table below:

They are 49 outcomes since the number of possible outcomes when the upper limit of goals per match is 6 are 7. You have to include 0 since that is a possible number of goals for any of the teams.

### Choose the goal score with the largest joint probability

From the table, you can see that the outcome with the highest probability is 1 goal at home and 1 goal away. However, that interpretation is only good for __Over 2.5 goals prediction and under 2.5 goals predictions__.

The correct-score prediction is, therefore, an area that needs expert analysis of matches. Depending on your guts and instincts can lead to massive losses. This is actually the best correct score tips method out there.

To get accurate sure bet correct score predictions today you just need to visit the __pricing page of Surebet__ and choose one of the packages. They are very cheap but full of benefits.