Your Ultimate Online Betting Hub in 2019
In previous articles, we’ve looked at odds and probabilities, then used this to understand the concept of value betting. Whilst discussing value, we touched on creating our own prediction model to allow you to generate your own probabilities and odds for certain sporting events. This can then be used to compare your odds with those of the bookmaker to identify value in the market and (touch wood) ensure sustained profit in the long term. In this article, we go through the steps required to create our own football (soccer) prediction model using Poisson Distribution, as well as look at some of the limitations of this approach.
So what is Poisson Distribution? If you Google it, you get back a lot of scary definitions that are very difficult to understand, such as “Poisson distribution is the probability of the number of events that occur in a given interval when the expected number of events is known and the events occur independently of one another”. What this basically means is that when we know the average number of times that an event will happen, we can use Poisson to calculate how likely other numbers deviate from this average.
Luckily though, we don’t need to fully understand the concept, the formula or how to calculate it because Microsoft Excel has a formula which can work out Poisson automatically. All we really need to know is that it can be used to calculate the probability of outcomes for a football match, which in turn can be turned into odds which we can use to identify value in the market. This covers a number of goal based markets such as Match Outcome (1×2), Correct Score, Over / Under Match Goals, Both Teams To Score and Asian Handicap. There is plenty of more in depth reading into Poisson online, but we won’t be delving into that level in this article.
Although it has its limitations and faults, Poisson is a useful starting point to understand the fundamentals of creating your own odds. It can work as a standalone model which you use to advise your betting, or it can be used to understand the basics before going on to explore further, more complicated methods. It also has applications to other sports, but in this article we will just look at football.
As you begin to create your own odds, check them against our top-rated football betting sites with the best odds below:
As a quick summary, what we are going to do is take historical results to calculate the number of goals teams score and concede. These averages are compared to the league average and used to create values for attacking strength and defensive strength for every team, which are then turned into goal expectation figures. This metric is put into a Poisson Distribution formula which works out the probability of every result when two teams face each other. We then take these probabilities to create our own odds, compare these against the bookies’ odds, then identify where there is value in the market because the bookies are offering more generous odds that we’d expect. Simple!
The beauty with a method like this is that there are a number of different points during the process where you might decide to try a different value as an input or may want to include something else in the calculation. You may even choose to calculate goal expectation in a completely different way, for instance, by using Elo ratings which ranks all teams against each other – as teams play each other, their respective rating will increase or decrease based on the outcome of the result – and will be covered in a later article. That is perfectly fine and will help you develop and refine your predictive model during its lifetime.
The below is a slightly modified version to the method I used throughout the 2013/14 season – after all, I don’t want to give all of my secrets away – however, it will allow you to create your own predictive model if you follow these steps.
Poisson = (x, mean, cumulative)
x = Number of goals
Mean = the probability of that team scoring a goal i.e. goal expectancy
Cumulative = Is set to FALSE, so that the formula returns a value exactly equal to x (number of goals)
Obviously we don’t have cell references in this example as you’d find in Excel, but the formula should still make sense. If we use 0-0 as an example, the Poisson Distribution formula would look like this:
If we use the formula for all of these scorelines up to 10-10 and use a matrix, then something like this will be created. As you can see, the most likely scoreline is 2-0 to Arsenal (15.93% probability), closely followed by 1-0 to Arsenal (15.77% probability).
In the search for value, you may also consider looking at other markets which are goal based. For example, Over / Under 1.5 Goals, Team to Win to Nil, Double Chance (win and draw) or Asian Handicap, although the latter does require a bit more work. However, the below table gives the probability of a few of the most common markets by using the principle of the above bullet points:
And there it is, your own predictive football model. Obviously I will give a couple of caveats at this point as no predictive model can be spot on or take into account every factor in the world. Some like Poisson Distribution, others don’t. I’ve personally found that it has been profitable for me over the last season, but that’s not to say that it will continue to be or that there isn’t a better method out there. A few points to consider are:
I hope that this has been useful and you have plenty of hours of fun with your new spreadsheet. Remember, always check and double check the figures, do your research, don’t bet what you can’t afford to lose and ask questions should your model be too dissimilar to the market as that could indicate an issue. Happy betting!
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