Expected Goals (xG) in Football Betting: How to Profit

Expected Goals (xG) has changed the way smart bettors analyse football. Instead of relying on scorelines, pundit opinion, or gut feel, xG helps you measure the quality of chances and spot when the market has misread a game.

In this article, I’ll explain what xG means in football betting, how it works, and how to use it to find value others miss.

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 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 video below, 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 xG Matters in Football Betting:

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 analyse a game
3. Reveals the true performance (not results-based)
4. It can identify value in the betting markets (can pinpoint market overreactions)

What Is Considered a Good xG in Football?

One question that comes up a lot is what actually counts as a “good” xG figure.

As a rough guide:

• 0.50 xG = very few quality chances created
• 1.00 xG = average attacking performance
• 2.00 xG = strong attacking display
• 3.00+ xG = dominant performance

It’s important to compare xG against the opposition too. A team producing 1.8 xG while conceding only 0.4 xG has generally controlled the match, even if the final scoreline doesn’t reflect that.

How I Use xG to Spot Value Bets:

Over the years, I’ve personally used xG to flag teams that the market undervalues. For example, when a team loses but posts strong expected goals (xG) numbers, I make a note…

Bookmakers often overreact to scorelines without fully considering the performance behind it. This is where the edge comes in. I don’t always act straight away, but I’ll watch the next game closely. If the price looks wrong, that’s when I step in. It’s simple but effective (I’ve found some of my most profitable trades this way).

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 graphic below, 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 is 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 statements was 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.

Today, the two xG resources I use most are Understat and FootyStats.

Understat is excellent for team and player expected goals data. At the same time, FootyStats combines xG with a wider range of betting-focused statistics such as BTTS percentages, goal timings and league trends. Both are free to use and are among the best football stats resources available in 2026.

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 than 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, 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 regardless of which football stats site you are using.

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.

Examples of Typical xG Values

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.

How Useful Is xG for Football Betting?

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. A team can consistently produce good xG numbers but still struggle if key players are injured, tactics have changed, or motivation is low. This is why I always combine xG with team news, form and watching matches wherever possible.

In the video and example above, you can see how powerful expected goals can be. Expected Goals is one of the most useful tools I’ve ever come across in football betting. When mixing it with your own match viewing, form analysis, and player news, it can give you a huge edge. The key is not to blindly trust xG, but to use it as part of a bigger picture. I’d encourage anyone betting regularly to start tracking xG. Over time, you’ll see the benefits in your results. If you want to dive deeper, check out the full football trading course I’ve put together.

Related: Top Goalscorer Betting Explained (Example and Strategies)