Expected Goals Stats and Football Betting

You may have heard of expected goals (sometimes known or written as xG) and wondered exactly what it is. Or you may have a good understanding of xG but never fully considered how it could aid in your football betting.

Either way, read on as we attempt to shed more light on this stat which is as loved by football data analysts as it is revered by (some) pundits!

Expected Goals Explained

Expected goals is a measure calculating a value between 0 and 1, and is based on whether the shot taking place will result in a goal or not. 0 means there is no chance of a goal being scored, while 1 implies a certain chance of the goal being scored.

There are many different factors and historical data used to determine the calculation, which are shown in more detail below. What the data allows us to do is work out how many goals a particular team should have scored in a game based on the chances they had. You can use this to work out if they have been unlucky, or whether they were beaten fair and square because they didn’t create enough chances.

Expected goals data can also be used to form an expected point stat too, which is the expected number of points a team should have won throughout the season based on the number of goals they should have scored. Calculations are made based on goals for and against, with that then being used to work out how many games won that would have given them.

What is the Calculation for Expected Goals?

Here are the six main components that are used to determine what the XG figure is for a shot on goal:

1. Body part – was the shot taken with the player’s strong foot, their weak foot, a header or something else? 
2. The passage of play – Is the shot taken from open play or is this a set-piece situation?
3. The distance from goal – Is the shot from close range or far out? Generally speaking, players are more likely to score the closer they are to the goal
4. Angle from goal – Is the player directly in front of goal, towards the side or from a very tight angle. The tighter the angle, the more difficult the shot will be and the less chance of scoring there is
5. How was the chance created – Is the shot from a through ball where the player is going in on goal, a cross into the box, a deflection, or something else? 
6. The actual shot – Is this a clean chance, a rebound, has the player beaten a man before shooting?

These are just the basics of the XG model, some companies who work these out go a lot more into detail, including what the defensive side of play looks like. This includes judgment on the goalkeeper, if players are close by to block or out of position and much more.

As you can see, the methodology behind this is very complex, but everything that has been listed above makes sense. A shot from the strong foot in open play, close to goal, directly in front of goal that is a clean chance has more chance of going in than many other shot types.

How to Use Expected Goals When Football Betting

XG data gives you a better look at recent games than the score line alone, and this is how you can use it to help when betting.

Example:

Manchester United have taken 1 point from their last three games.

This would be deemed as a bad run of form for them, and because of that, the bookmakers have priced them up at a bigger price than normal to win their next game.

The XG data shows that they have comfortably been better than their opponents in their last three games. This tells you that they are not playing poorly, but have been unlucky and are still playing well despite getting just one point.

From this data you would take that Manchester United are a value bet because of their price, the data suggests they are playing as well now as they have at any time, regardless of the points they have picked up.

You should only use XG data as a guideline to show how teams have been performing but if this matches what you believe will happen in a game then it adds additional strength to your selection.

Something else to look out for is teams creating chances when you are betting on the total number of goals. If the XG stats point to them creating many good chances, a higher number of goals in their games is more likely. Those creating poor quality chances, even if they are having a lot of shots on target, are less likely to score, and can be used to bet ‘under’ on the goals line. 

That's it, in a nutshell, so next time you see the xG stat flash up after each game on Match of the Day, it should make more sense and can even be considered in your future betting strategies.

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