Expected Goals (xG) quantitatively measures chance quality, a concept that is widely used in the sport.
Watching a game we can intuitively tell good chances from bad chances based on a variety of factors. How close was the shooter to goal? Was it from a good angle to the goal? Was it a one-on-one? Was it a header?
xG takes these factors - and others – into account and calculates how likely it is that a particular shot will be scored. For example, if a shot with a specific set of characteristics is likely to be scored one time in every 10 it will be worth 0.10 xG. These calculations are based on extensive historical shot data (over 300,000 shots from the Opta database at the time of writing) and are adjusted for different leagues.
The metric reflects how Opta analyzes games; the team that creates the higher quality chances is usually considered having been "the better team." An xG model gives a quantitative measure to the quality of scoring opportunities and adds additional context to a player or team’s shots that goes beyond raw shot and shot on target totals.
Expected Goals is typically a more consistent measure of performance than actual goals. Whereas goals are relatively rare events that come and go in stretches, a team or player’s xG output tends to fluctuate much less from match-to-match. Clearly the goals that are actually scored are the ones that win points, but xG gives us more context for evaluating team performance.
To learn more about Expected Goals, visit OptaPro's blog.