Statistics have a key part to play in modern football, enabling fans, pundits and even managers to give greater weight to their arguments and analysis.
Football is a game of opinions but figures and numbers are also key to gaining greater insight into the sport and one of the newer metrics being used is expected goals, often abbreviated as ‘XG’.
Here is a look at XG, what purpose it serves and how it is influencing the game today.
What Is XG?
At its core, XG or expected goals is simply a statistical metric used to quantify the quality of a goalscoring opportunity and the likelihood of that chance being converted into a goal.
XG models use historical information to estimate the chance of a goal being scored and this is measured on a scale of zero to one. On this scale, an XG of 0.8, for example, is a pretty high value and we would generally expect a shot with this value to be scored eight in every ten attempts.
Having been first officially introduced by Opta back in 2012, it can be applied to a match in isolation or averages can be taken to work out the XG of a team or individual player across the course of a season.
It is now used widely by pundits, broadcasters and journalists as well as managers and coaching staff to more accurately assess performance.
How Is XG Calculated?
As mentioned, an individual chance is given a value between zero and one when it comes to measuring XG and XG models often use historical data to calculate the chance of a goal being scored.
But there is a lot taken into consideration when making this assessment. For example, whether the shot was taken with the head or foot will be factored in along with the angle and distance of the shot and the type of pass or assist leading up to the shot.
It does not take an expert football analyst to know that a central shot inside the box will have more chance of finding the net than an angled shot from distance but XG models take this to the next level, often factoring in things such as pressure from defenders and goalkeeper position.
When looking at a match rather than an individual chance, the average quality of chances created is assessed, giving a figure of how many goals a team should have scored in a game.
Why Is XG Important and How Is It Influencing the Modern Game?
Over the course of a season, a team may not be scoring many goals but still has a high XG.
This suggests firstly that the team is getting into the right positions and creating decent chances but perhaps their strikers are lacking in the finishing department.
But XG can also be used to make predictions and this could also suggest that it is only a matter of time before the team starts scoring more regularly, and potentially winning more matches.
On the flip side, if a team has a low XG and exceeds that figure, it could imply they have quality strikers able to make the most of less clear-cut chances.
It has become as important a metric as total shots or possession when looking at the performances of teams and players, and can be used by punters or journalists to predict future trends – but also intrinsically by clubs to more accurately assess player performance or the performances of future transfer targets.
Can XG Be Misleading?
As with all metrics linked to football analysis, XG must also sometimes be taken with a pinch of salt and fans, pundits and journalists alike should never forget to look at the bigger picture.
In some circumstances, for example, a higher XG figure does not necessarily mean a team should have won that match – it refers to the quality of chances being created and the likelihood of a goal being scored.
When a team goes behind in a match, the onus is on them to create chances and go in search of an equaliser, potentially raising their XG figure and lowering the XG of the winning team, who have spent more time defending their own box.