xG has fast become part of the football vocabulary – the data a source of inspiration for coaches, players, broadcasters and pundits around the world.
The terminology has changed the landscape of the game, entering the mainstream domain with the ever-evolving analysis switching discussion from opinions to a more sophisticated view among managers and fans alike.
But what does it all mean?
If you’ve been wondering, but too shy to ask, don’t fear: here is what is behind the metric at the forefront of football analytics.
What does xG mean?
Gone are the days of sitting back and lamenting a player missing a “sitter”. Now, those chances are measured to provide context and possibly curb expectations in front of goal.
Well, first of all, Expected Goals (xG for short) is the advanced metric which measures the quality of a chance by calculating the likelihood that it will be scored from a particular position on the pitch during a particular phase of play.
xG is based on several factors from before the shot was taken. xG is measured on a scale between zero and one, where zero represents a chance that is impossible to score and one represents a chance that a player would be expected to score every single time.
How is it calculated?
When it comes to calculations, there are various factors at play: distance from goal, angle and body part – was a shot taken with the head or foot?
The predictive model assesses every goal-scoring chance and the likelihood of scoring. In theory, if a chance has 0.2xG it should be scored 20% of the time. If it has 0.99xG, the shot should be converted 99% of the time. You get the picture.
The more difficult the goal the lower the xG. Take Ben Garuccio’s ‘scorpion goal’ for Western United in the Isuzu UTE A-League on Sunday. His viral attempt had an xG of 0.52. Socceroo Riley McGree also scored from a scorpion kick during his time with Newcastle Jets in 2018 and that has an 0.57xG.
For a close-range shot from a central position, the xG would obviously be higher than a header from an acute angle.
Here’s the factors that base the xG calculation via Opta:
- Distance to the goal
- Angle to the goal
- One-on-one
- Big chance
- Body part (header or foot)
- Type of assist (throughball, cross, pull-back etc)
- Pattern of play (open play, fast break, direct free kick, corner kick, throw-in etc)
Why should we care?
Well aside from helping to assess individuals, Expected Goals provides an evaluation of teams while also predicting future performances.
No longer can you say “he should’ve scored a hat-trick today!” The numbers paint a clear picture. Or if a coach anywhere in the world – from Jurgen Klopp to Tony Gustavsson – is making an excuse about his attack, well, we can see, quantitively, that the attack actually was all there minus the missing striker.
xG is also useful in analysing and illustrating attacking and defensive trends.
So the next time you find yourself at a pub or at home on the couch, shouting at a player for failing to find the back of the net, be sure to ask yourself, before arguing: I wonder what the xG would be for that?
