Soccer Expected Goals (xG) Explained

Many old-fashioned soccer fans disregard expected goals (xG). However, if you want to take your soccer betting to the next level, you need to get up to speed on the latest metrics and statistics.

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Below, we cover all the ins and outs of expected goals and outline how to calculate xG. We also explain how bettors can utilize xG to support their soccer wagers and enhance their chances of making a profit.

What is Expected Goals (xG) in Soccer?

Put simply, the expected goals metric measures the probability of a shot resulting in a goal. The model relies on historical data from thousands of similar shots to predict the likelihood of a goal, using a scale between 0 and 1.

For example, a shot with an xG value of 0.1 would typically be converted once in every 10 attempts. At the opposite end of the spectrum, a shot with an xG value of 0.9 would generally turn into a goal nine times out of 10.

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How to Calculate Expected Goals (xG) in Soccer

There are lots of different xG models out there, but they all use the same key factors to calculate the value of a shot. Here are the main factors that are taken into consideration when it comes to predicting the likelihood of a goal.

Distance to the goal

Angle to the goal

Which body part was used

Which type of assist was provided

By collecting historical data from shots with similar characteristics, xG models can attribute a value between 0 and 1 to every shot. The final value presents the probability of the shot resulting in a goal.

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How Bettors Can Utilize xG in Soccer

The expected goals metric can be extremely useful for soccer bettors. Based on xG data, bettors can gauge which players and teams are likely to score more goals, and which players and teams are likely to struggle offensively.

Let’s take the Premier League as an example. During the 2022-23 campaign, Manchester City amassed an xG value of 84.32, meaning they were expected to score just over 84 goals that season. This was the highest xG value in the league.

Meanwhile, Wolverhampton Wanderers had the lowest xG value with 35.13, meaning Man City was expected to score 49 goals more than Wolves. This data highlights the gulf in offensive power between the teams.

Team xG data can be used to help with a wide range of betting markets, including over/under goals, handicaps and both teams to score.

Individual players also amass xG throughout a season, so bettors can use this data to aid their bets. If you enjoy making use of soccer player props and goalscorer markets, utilizing xG will only improve your chances of winning.

Expected goals against (xGA) is another helpful metric for soccer bettors. Instead of calculating the expected number of goals for a team, xGA calculates the number of goals that a team is expected to concede.

Check out who has scored the most goals in a Premier League season next.