Guide to Expected Goals in Football (xG) | Football Betting Tips

Expected Goals has the changed the way we bet on football, for a long time it was a well kept secret of the betting elite. In today’s article we look at how Expected Goals (xG) is revolutionizing football analysis and betting!

xG will massively improve your football betting and trading. It removes all biased opinions in the football world and measures the true probability of a goal being scored Over the course of 90 minutes. xG shows who really came out on top and is an excellent tool for football form, and betting!

What Is xG?

Expected Goals (xG) is a statistical measure used to evaluate the quality of scoring chances and the likelihood of goals being scored. Like with anything new, most people are reluctant to trust the data. xG however is a very reliable tool for understanding just how a football match was played.

It is a much better representation of how teams fared against each other in comparison to merely looking at the result! 

xG offers the probability of a goal being scored from each chance.

It ranges from 0 to 1, with 1 being the highest because that’s a goal!

An easy example is a penalty – the average penalty has an xG of close to 80% (0.78 xG officially); that means for every 100 penalties taken 78 will be scored. This is based on extensive data collected over many years of football matches.

In the below video, I explain how xG is calculated and why it’s so important…

Key points covered in the video include:

• 0:34 – What Expected Goals (xG) means.
• 2:03 – How the xG ratings work and how xG is calculated.
• 5:15 – How to use Expected Goals.

Why use expected goals (xG)

There are a lot of benefits to using the metric of expected goals for betting and analysis.

1. Eliminates any bias you may have towards a team
2. It is an objective way to analyze a game
3. Reveals the true performance (not results based)
4. It can identify value in the betting markets (can pinpoint market over reactions)

Using Expected Goals (xG) To Find Value When Betting

xG can really give you an edge when betting, be it on the win or predicting a draw.

Look at this example below. Southampton beat Manchester City 1-0 recently, but as you can see in the below graphic – Manchester City didn’t play badly, they just failed to score. It was just one of those random things that happen in sport from time to time when a team massively on top doesn’t win.

It happens.

Many retired footballers become pundits, and some of them are quite lazy. They take the easy option and say things like “oh that was a big shock for City” or “they’re slacking off towards the end of the season.” Neither of these statement were true.

They played superbly in fact, and why is this important?

Because when looking for possible bets or trades for their next fixture – even though they had lost to Southampton it was obvious to anyone using xG that they had been playing very well. The market would probably overreact to this result despite the performance.

Applying xG for future performances

What did Manchester City do in their next two games after this? They won 5-0, and 5-0:

As you can see, Expected Goals (xG) is a simple way to see is a team playing well. xG said that was coming.

The site I use to study xG is Infogol. They have everything you need to see and provide an in-running xG service too. Which is very helpful from a live trading point of view.

Want free betting lessons? Sign up here! 

Any Criticisms of Expected Goals?

The biggest criticism of expected goals is that is doesn’t take into account the quality of the player shooting or in goal. That for example when Messi takes a shot from outside the box it is much more likely to be a goal then when  Declan Rice takes a shot.

That can be true, but xG takes into account a whole host of variables and with years of data backing it up and it shouldn’t take into account each and every player’s ability. This is something that is variable, players come and go, but we need years and years of data to back up the correct probabilities.

Whilst xG doesn’t account for individual player abilities, the model’s strength lies in its reliance on extensive, long-term data. This ensures its reliability as a predictive tool.

How Is Expected Goals (xG) Calculated?

Some variables xG focuses on are:

• Distance from goal: Closer shots have higher xG values.
• Set piece or open play: Different types of play affect scoring chances.
• Angle of shot: Shots from better angles have higher probabilities.
• Shooting part of body: Headed shots generally have different xG values than footed shots.
• Origins of the chance: Whether the opportunity came from a rebound, through ball, etc.

Who Created Expected Goals (XG)?

It is not known who exactly created the methods and metrics of expected goals. Although there have been a few noted contributors to bringing into the mainstream:

1. Opta Sports – one of the leading sports analytics companies, played a crucial role in popularizing xG. They have been pivotal in collecting and analyzing football data, offering detailed metrics like xG to teams, media, and fans.

2. Sam Green – a football analyst formerly with Opta, is often credited with refining and promoting the xG model in its early days. His work helped bring xG into mainstream football analysis.

3. Michael Caley – a data analyst and blogger, contributed significantly through his detailed explanations and visualizations of xG on social media and through various publications.

Conclusion

In this article we have covered the meaning of xG in a football game.

xG is a complex model that is very accurate even allowing for some criticisms.

You don’t need to fully understand the calculations behind xG to use it effectively. When combined with other factors such as form, player injuries, team tactics, style match ups. It can be an excellent addition for finding value in the sports betting and trading markets.

In the video and example above, you can see how to use it properly. Expected goals can be a very powerful tool when betting on football.

Related: 3 Football Betting Systems Built on FACTS