Metric analysis

xG: the new data metric taking the world of football by storm

Every season a new data metric or analytics tool is used by top clubs to optimize performance. Over the past few seasons, xG has risen to the top. Here we look at what it is and how it is calculated.

What is xG?

xG stands for Expected Goals and it is the probability that a player will score depending on the situation he is in. xG can be implemented for one player or an entire team and it lets you see how effective they are in front of goal.

xG values ​​range from 0 to 1 and the higher the value the more likely the shot is to be a goal. A good example of this is a penalty that has a value of 0.76, meaning a higher chance of scoring.

Each xG season becomes more popular, with Sky now implementing the metric into its pre-game, during-game and post-game analysis.


How is xG calculated?

There are what seem to be endless factors that contribute to the calculation of xG. The most recognized include:

  • The shooting location
  • The number of defenders and the positioning around the shooter
  • The quality of the pass to the shooter
  • Type of shot
  • Shot distance

These are all used to decide the xG value of odds throughout a game.

Looking at it from afar, away from all the complicated numbers and statistics, xG is pretty straightforward. We all know a shot from the halfway line is less likely to go into this one in the six-yard box, but the data metric just puts a number to those shots.

The combination of xG totals throughout a season for a player/team gives the coaching staff an idea of ​​whether they are underperforming or overperforming. An example of this is Kevin De Bruyne who scored 15 goals last season but only had an xG of 5.95 meaning he was overperforming his xG of 9.05.

Depth and reliability of xG

As football is a low scoring game, one might think that this data metric lacks depth and reliability. However, the people behind him have access to over 2.5 million shots and 66,000 players, meaning there’s an abundance of depth rather than a lack of it.

Regarding reliability, as everyone knows Soccer is unpredictable and goals can be produced from several different outcomes. So xG can most certainly track the underlying performance of players/teams, but it can’t tell if a player will score, but rather how likely the goal is.

To learn more about xG, Opta have created a video to explain in more detail, or to see for yourself how the players fared regarding xG last season Check out Understat.

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