Odds

## How much value is there in soccer betting markets ?

## Introduction: Finding Value in Soccer Betting

The world of sports betting, especially in soccer, can seem complex and confusing. However, with the right strategies and a clear understanding of key concepts, it’s possible to turn this activity into a profitable opportunity.

In this article, we will explore how to identify value in soccer betting markets, focusing on one of the most crucial concepts: Expected Value (EV). We’ll also guide you through the steps to calculate this value, along with the essential statistics and metrics to uncover the best opportunities. Whether you are a novice or an experienced bettor, this introduction will equip you with the tools you need to improve your bets and maximize your profits.

### How to analyse odds using Expected Value

Our Blog already has many articles covering **Expected Value**, or EV, so let's just summarise it briefly with an equation:

**Expected Value = (Bookmaker's odds / True odds) - 1**

If the true odds are 2.00 and the bookmaker’s odds are 2.10, this means the EV is 0.05, or 5%. If the true odds are 4.00 and the bookmaker’s odds are 3.50, the expected value is -0.125, or -12.5%. Serious bettors are only interested if the expected value is greater than 0%, or when the bookmaker offers odds that are longer than the true odds.

Of course, knowing what the true odds are is another matter altogether. Sports betting is not like dice or roulette and the markets are complex systems, for which there are no simple algorithms that will tell you what the true outcome probabilities are. We have to estimate them via data modelling and perhaps a bit of intuition as well. The better your model, the closer your estimated probabilities will be to the true probabilities.

**Pinnacle’s model** is a combination of their own data analysis and the market information they acquire about their customers’ models, meaning it’s one of the best at estimating true probabilities. Of course, it won’t always be right, but on average it’s surprisingly good. For example, about 50% of their prices of 2.00 (after you’ve removed their margin) win and 25% of their prices of 4.00 win.

Individually, it’s impossible to know which odds were closer to the true odds and which were not so close, but on average, the errors are broadly cancelled out.

### How to apply Expected Value to soccer matches ?

As the closing odds before a soccer match starts contain more information about the match than the odds when Pinnacle first published them, on average the closing odds are closer to the true odds than the initial ones.

We might propose that the amount by which the odds move provides a measure of how much Expected Value there was available in the **initial odds**. This is not to argue that the **closing odds** are always correct, nor that the initial odds are always incorrect.

Instead, this means that the ratio of the two can be used as a proxy measure of Expected Value, given that we can’t know what the true odds are. This can be formulated as follows:

**Expected Value = (First odds / Last odds) - 1**

Naturally, sometimes both the initial odds and the closing odds will be shorter than the true odds, sometimes they’ll both be longer, sometimes the initial odds will be longer than the true odds and the closing shorter, and sometimes the opposite will occur. However, on average the ratio of the two should give you a good idea of how much Expected Value existed in the initial odds.

With this assumption in mind, how much Expected Value exists in soccer betting markets? For a sample of 158,092 soccer matches and 474,276 home-draw-away betting odds, I divided Pinnacle’s initial odds by their closing odds, having removed their margin from the closing odds, and subtracted one.

So, how many odds had Expected Value greater than 0%? The figure was 29.7%. That’s actually quite a surprise, as it means nearly a third of Pinnacle’s initial odds actually hold some Expected Value.

### How meaningful is Expected Value in soccer betting markets ?

We might expect there to be more occurrences of low Expected Value (e.g. 2%) than high Expected Value (e.g. 20%). But how much more? I ranked the size of the expected value for each bet in ascending order, then calculated a cumulative percentage.

For example, 29.7% of odds held EV greater than 0%, but this falls to 21.7% for EV greater than 2%. By the time we reach the threshold of 10%, only 6.6% of odds will hold such value on average, and at 20% it’s just 1.8%. This is how such a trend appears on a graph:

Evidently, there is a lot of expected value to be found in the soccer match betting market. However, don’t expect a lot of big gifts. The availability of increasing EV falls exponentially, meaning the greater the expected value, the far less of it you will find, assuming you even know where to look.

Of course, the much bigger problem for bettors is knowing the expected value is there in the first place. Using this proxy measure, you won’t know that it was there until Pinnacle have published their closing odds and by then, the initial odds have gone.

Nevertheless, if you do have a forecast model that works and can reasonably estimate the true odds, you now know that when Pinnacle publish their initial odds, there is (in theory) a lot of potential for making a substantial profit.

Saturday, August 10, 2024

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