Expected goals (xG) is a tool to value the probability of a shot resulting in a goal. Each xG value is the chance of that shot being scored. For example: 0.156 xG = 15.6% likelihood of that shot being scored. By having a database of shots a xG model will work out how important each variable is in a shot being scored. The database takes into account a variety of variables of the shot which will be covered later.
Expected Goals shows the quality of one shot or a teams shots in a game or a player’s over the season.. Just looking at the number of shots in a game tells you very little because it doesn’t tell you the quality of those shots. A team can have 30 shots in a game but they could all be from wide angles with 11 defenders in front of them. While another team could take 3 shots from within the six yard box after winning the ball in the final third and playing a throughball and dribbling round the keeper. The second team is far more likely to win with these shots.
Expected Goals models consider factors such as:
- Location of Shot
- Type of Assist
- Counter Attack?
- Shot with Head or Foot
- Ball won in final 3rd?
- Minute of shot
- Game State
- Free Kick?
You can add up the expected goals of each team’s shots from a game or a player’s shots over a game or season. It can show the performance of each team and if they under or over performed by scoring at a higher or lower rate than expected.
Be sure to follow our data twitter – @CA_Viz – where you can request data and graphics.
Also, we now have player and team Expected Goals data on our site which we are going to update weekly. We’re always adding leagues and data so keep checking! Pages like this one.
I hope you understand the theory of xG if you didn’t before. Please visit the great site 11tegen11 for more information and better analysis and examples about xG.
All feedback appreciated: sidelineteamtalk @ gmail [dot] com and follow me on twitter @SL_TeamTalk