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Using Expected goals (xG) to influence the way we bet on football

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Expected goals (xG) is a relatively new metric that has made its way into the world of football. This xG can give you a much clearer understanding of a team’s performance during a game rather than just merely looking at the score-line, the possession or shots data. This xG data can then ultimately be used in your analysis of teams and aid you in your quest for value in the football betting markets.

What is Expected goals (xG)?

Expected goals is statistical measure of the quality of chances created by teams during a football match. Every shot at goal is given an “Expected goal value”. Obviously not all shots have the same chance of becoming a goal, the better chances need to be given more credence when analysing a match. xG is expressed as a value between 0 and 1, 1 meaning a goal would be expected to be scored 100% of the time from the given scenario. If we take a penalty chance for instance, around 76% of penalties are converted into goals in the Premier League, meaning an xG value of 0.76 is given to the team who are awarded a penalty.

These calculations are generally based on several variables such as; distance from goal, build up play, opposition presence, whether it was a headed chance or whether it was classed as a big chance etc. The more variables an xG model takes into account, the more accurate it will be. Some models may just derive an xG rating for a shot based on the distance from goal, whilst some more advanced and accurate models may take into account the number of opposition defenders closing down the shooter. This is one of the reasons why you may have seen different xG figures from different sources regarding the same fixture. is good source for xG across the top major leagues in Europe, they use more than ten parameters for each shot to help give them an accurate xG figure.

xG Glossary

xG - no. of Expected goals a team or player would expect to score in the match.

xGA - Expected goals against: the number of goals a team would have expected to concede.

xA - Expected assists: the sum of expected goals resulting from shots after a player’s key pass.

xG90 - Expected goals per 90 minutes.

xA90 - Expected assists per 90 minutes.

xPTS - Expected points for a team during the league campaign.

Using Expected Goals to Help Influence Our Betting

Expected goals can be used in a variety of ways to improve your edge in the betting markets. The main use of xG is to analyse the form of a team based on their performances rather than just the end results of their games.

The table below shows Arsenal’s stats after nine games of the 2018/19 Premier League season. At this point they had scored over eight goals more than expected (8.44) and have almost eight points more than expected (7.60) in the league.


The next three games in Premier League saw Arsenal fail to pick up a win, drawing all three. Albeit one of the games was against a very good team in Liverpool. Plus they failed to beat Crystal Palace and Wolverhampton, two games in which they were odds-on favourites.

Over time you would expect a lot of teams/players who are outperforming their xG to, at some stage, revert back to the mean but it is certainly not always the case. There are of course, teams who will stay ahead of their xG for an entire season or maybe longer. During the 2017/18 Premier League season Manchester United conceded just 28 goals which was the bedrock for them securing second place in the league. Their xGA for the whole season was 43.54, a huge 15.54 goals difference. This difference can easily be explained by the brilliance of David De Gea in goal and really does show what a great season he had. Factors such as having De Gea in goal should come into your evaluations when looking into xG and applying it to your betting.

xG can also be used to highlight certain player performances and see which players are being highly influential. The 5th highest goal-scorer last season was Raheem Sterling, he was berated as a player who should have scored even more goals than he did. But in reality, his xG for the season was 18.83, more or less in line with his 18 goals scored.


In summary, expected goals can really help with your betting in terms of being able to unbiasedly judge team and player performances. It can also assist you in predicting future trends throughout different leagues. xG cannot be solely reliable however and you need to combine it with your existing football knowledge when making your choices.

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