How to price a soccer match

Why should you price soccer matches?

In order to identify value bets, you need to compare the odds you are betting on with what you believe to be a more accurate reflection of the true probability for an outcome. If the available odds underestimate the chance of an outcome in an event compared to your estimate, this will provide you with positive expected value.

While this is a simple enough concept to understand, establishing reliable data to compare against the bookmakers’ odds is where most bettors will fall down. Comparing odds will certainly help you find the best odds to bet with, but creating your own probabilities and comparing them against the market is what will help you find the right option to bet on.

A lot of people fail to recognise how difficult winning in betting actually is, and you’re not going to start finding value bets as soon as you begin pricing matches yourself. However, you need to start somewhere and at the very least, pricing matches will help you improve your understanding of probability. Once you develop your knowledge, get access to more reliable information, and experiment with various inputs and pricing methods, you may begin to find legitimate betting opportunities.

While this article will cover how to price a soccer match, it’s important to note that you don’t necessarily have to do the ‘heavy lifting’ of pricing a market yourself. Some people will choose to trust the market, using information provided by an efficient bookmaker such as Pinnacle and look for discrepancies with others.

Finally, the prospect of essentially creating your own odds for a match with incomparable resources to a bookmaker’s will likely seem daunting. Indeed, the process requires you to put in time to learn, make mistakes, and accept inevitable failures. However, if you’re willing to persevere then there is something to be gained from it.

How do you price a soccer match?

In order to help explain why pricing a soccer match is important if you want to bet on it, we have used a simple example to show how it could be done. It should be noted that this approach has plenty of flaws (which will be outlined later on in the article) and cannot help you find value in soccer betting markets when used by itself.

For the purposes of this article, we have used a Poisson model to create 1X2 odds for a match from final round of Premier League fixtures in the 2020/21 season. Using Infogol’s expected goals data for that season, we can calculate the Attack Strength and Defence Strength of each team for playing both at home and away.

This provides us with a relative measure of a team’s ability in terms of scoring and conceding goals by using the ratio of a team’s average and the league average. Using expected goals instead of actual goals will give a more accurate reflection of a team’s performances, as well as reduce the elements of randomness and luck capable of impacting on a 38-match season.

Here is the data on this front for the Premier League 2020/21 season:

Next, we need to break this down into the specific fixtures that we want to price up. We can then use the home team’s HAS and the away team’s ADS to calculate how many goals both teams would be expected to score.

This is what the process would look like for the match between West Ham and Southampton from Gameweek 38 of the Premier League 2020/21 season.

Therefore, West Ham are expected to score 1.792 goals and Southampton are expected to score 1.253 when they play each other at the London Stadium. However, the scoreline cannot be 1.792 – 1.253, so we need to find a distribution of probability across a range of outcomes.

We can use the Poisson function in Excel to calculate the probability distribution for the different number of goals that each team might score in a match (in this instance, we will use a range of zero to five). Using the example above, this is what the distribution will look like:

Team	0 goals	1 goal	2 goals	3 goals	4 goals	5 goals
West Ham	0.167	0.299	0.268	0.160	0.072	0.026
Southampton	0.286	0.358	0.224	0.094	0.029	0.007

Based on this, we can calculate the probability of individual scorelines. For instance, here is how to calculate the probability of a 0-0 draw:

We can use this technique to calculate the overall probabilities of a West Ham win, draw, and Southampton win. Below are the individual probabilities for every possible scoreline between the two teams according to our Poisson distribution:

West Ham goals	Southampton goals
	0	1	2	3	4	5
0	4.77%	5.98%	3.74%	1.57%	0.48%	0.01%
1	8.55%	10.70%	6.70%	2.81%	0.86%	0.20%
2	7.67%	9.59%	6.00%	2.52%	0.77%	0.02%
3	4.58%	5.73%	3.59%	1.50%	0.46%	0.02%
4	2.05%	2.58%	1.92%	0.67%	0.02%	<0.01%
5	0.74%	0.07%	0.06%	0.01%	<0.01%	<0.01%

NB: Percentages do not add up to 100% due to probabilities involving six, seven goals etc.

Based on this, we can determine that the probability of West Ham winning the match is 49.32%, a draw is 23.72%, and a Southampton win is 26.96%. This translates into odds as follows:

Outcome	Probability (%)	Odds
West Ham win	49.32%	2.03
Draw	23.72%	4.22
Southampton win	26.96%	3.71

In Pinnacle’s actual closing odds for this match, West Ham were priced at 2.17 to win, indicating that they were perhaps undervalued on this occasion.

Identify your weaknesses and maximise your edge

An important thing to remember is that while it may seem encouraging to uncover discrepancies, if the bookmaker is more accurate than you, you will likely still not record a profit with your soccer betting long-term.

At the same time, it can be tempting to start placing money on what you feel you have identified as value bets, but even with small amounts this can be a costly endeavour. Therefore, back testing is the most efficient approach to see how viable this method is.

Comparing the odds this model would have produced for past events and comparing them against Pinnacle’s closing line will help us assess how good this pricing strategy is, but you need to know not only whether the method works or not, but also why that is the case.

There are plenty of reasons why the expected goals Poisson model used above isn’t a good way of pricing a soccer match. Using last season’s data as opposed to using rolling data means it will quickly become outdated. Not accounting for transfers and managerial changes could easily skew the measure of a team’s strength and thus their chances of winning a match.

Indeed, for the sake of argument if we did uncover an edge using this model, it’s crucial to understand why. Is it just something that the bookmaker or other bettors haven’t considered? Is it dependant on when you place the bet? Can you improve the quality of the data to magnify the edge? Once you have established a legitimate edge and you know why it exists, it is imperative that you manage your bankroll to maximise it.

Naturally, the hard work isn’t over once you find a successful betting strategy and more commonly, that is actually the stage at which it begins. Unfortunately, some bookmakers will ban or restrict those that manage to make more accurate predictions than the odds they are offering.

This makes it even more important that you maximise your edge while you can and that you work to keep improving your model so you can test yourself at bookmakers where you won’t be banned or restricted, no matter how much you win. In case you need reminding, Pinnacle is such one bookmaker.