European Soccer Leagues Are Back – How to Use Advanced Stats to Gain an Edge

While sports in the US are still recovering and planning for their comebacks, all of the major European soccer leagues are already back in action. 

With Premier League, La Liga, Serie A and Bundesliga games being played every week, now’s a good time to familiarize yourself with advanced statistics in soccer and ways to use them to your advantage when testing out sports trading systems.

In this introductory article, we’ll take a look at the most popular advanced stat in soccer – expected goals.

Simple sports trading systems don’t work

While many sports fans in the US are already familiar with advanced stats in football, baseball and basketball, soccer is more of an unknown territory for most. The beautiful game has certainly lagged behind on that front as well, but traditionalists are fighting a losing battle, and solid analysis definitely relies on advanced stats these days.

And while we currently don’t have an actively recommended soccer trading system in use here at ScoreMetrics, we are constantly doing research to bring one out to the market. 

Earlier this year, we wrote about one failed experiment for an English Premier League system where we went in with the following hypothesis:

”With this system, we wanted to find out whether games where the visiting team has a very low win percentage and the home team has a winning record have a tendency of going under. Our hypothesis was basically that the public overvalues the over play in these types of situations, leading the contrarian approach of investing in the under to be profitable. Casual sports bettors often like to bet that games with their favorite teams will be high-scoring affairs, so this felt like something worth exploring.”

And we then concluded:

“Based on our years and years of experience, finding the truly great systems that steadily bring in big bucks usually doesn’t happen with such a simple set of rules. So, while this test did not result in us discovering a winning system, it points to various directions that we can research further to bring you a solid English Premier League package.”

Adding advanced statistics on top of these types of simpler rules could make for a more elaborate system. And expected goals (xG) is the most commonly used one for soccer.

Introduction to expected goals in soccer

Expected goals is used to determine whether or not a player or a team is scoring based on factors that are sustainable and thus giving a reason for us to expect more of similar offensive performances in the future. 

Instead of relying just on traditional counting stats, such as goals per game and shots per game, expected goals adds a lot of depth by taking into account where and how shots are taken from. 

Shots that are taken closest to the goal are obviously more valuable than shots taken from a distance, as scoring is much likelier from a close range. Models for xG vary between different sources, but the simpler models often use a zone-based system (for example, the 6-yard box, the penalty area, and outside the box), while the more advanced models use an exact number of yards away from the goal for each shot taken.

On top of this, factors that affect advanced xG models include the angle in relation to the goal where the shot was taken from, and whether the shot was a kick or a header, or if it came off of a cross or a through ball. 

Having the average expected goals for each team in a league gives investors a pretty reliable overview of how teams can be expected to perform offensively. Add to that the same for expected goals allowed, and you have a couple of advanced statistics that can give you a big edge in handicapping games.

Conclusion

Besides being useful for handicappers and sports traders, xG is also something that soccer teams are finding very useful. There has been a lot of hype around the stat in recent times – take a look at this article from the official Bundesliga site, for example. 

There aren’t many free resources out there that offer up to date, reliable xG data, so unfortunately investors either have to do some manual work or pay for their access to relevant data. 

On the other hand, this means that most bettors in the market are not currently using this type of data, which in turn provides us with a chance to find an edge in the market. 

To prepare for the return of sports and to learn everything you need to know about smart investing in the sports betting market, check out our head trader John Todora’s new book – “Zero Correlation Investing – The Score Metrics Secret”. It’s currently on sale for a limited time, so go get yours now!

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