Expected Goals (xG) is a statistical measure that estimates the probability of a shot resulting in a goal. It is calculated by considering various factors such as the location of the shot, the type of pass or dribble that led up to the shot, and the body part used to take the shot. The resulting number is expressed as a decimal between 0 and 1, with higher values indicating a higher likelihood of the shot being a goal. xG is commonly used in football analysis to evaluate a team or player’s performance and to predict the outcome of future matches.
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xG can be used in football analysis
One common use is to evaluate the quality of a team’s chances. By comparing a team’s xG for a given match to the number of goals it actually scored, it is possible to get a sense of whether the team was unlucky or lucky to score as many goals as it did.
xG can also be used to evaluate individual players. For example, if a player has a high xG per shot, it means that they are taking shots from high-quality scoring positions and are therefore likely to score more goals in the long run. Similarly, a player with a high xG per 90 minutes (the number of expected goals they would score over a full 90-minute match) is likely to be a more dangerous attacking threat.
In addition to these uses, xG can also be used to make predictions about the outcome of future matches. By analyzing the xG of both teams, it is possible to get a sense of which team is more likely to win, draw, or lose the match. This can be useful for making betting decisions or for simply getting a better understanding of how a match is likely to play out.
- The location of the shot is a major factor in the calculation of xG. Shots taken from closer to the goal are more likely to result in goals than shots taken from farther away.
- The type of pass or dribble that led up to the shot can also affect the xG. For example, a shot that follows a through-ball (a pass that splits the defense and creates a scoring opportunity) is likely to have a higher xG than a shot that follows a simple pass from the midfield.
- The body part used to take the shot can also impact the xG. Shots taken with the head are generally more likely to result in goals than shots taken with the feet, for example.
- In addition to these factors, the xG model may also consider other factors such as the defensive pressure on the shooter, the angle of the shot, and the height of the shot above the ground.
The specific algorithms used to calculate xG vary from one model to another, and some models may consider additional factors or weight the factors differently. However, the basic principles described above apply to most xG models.
- One common use of xG is to evaluate the overall quality of a team’s attacking play. A team that generates a high xG over the course of a season is likely to score a lot of goals, while a team with a low xG may struggle to find the back of the net.
- xG can also be used to evaluate the efficiency of a team’s attack. For example, if a team has a high xG but a low number of actual goals scored, it may be considered “unlucky” and likely to score more goals in the future. On the other hand, a team with a low xG but a high number of actual goals scored may be considered “lucky” and likely to score fewer
goals in the future.
In addition to evaluating teams, xG can also be used to evaluate individual players. For example, a striker with a high xG per shot may be considered a player who takes high-quality shots and is likely to score more goals in the future. Similarly, a defender with a low xG against (the number of goals the opposition is expected to score when that defender is on the field) may be considered a strong defensive player.
xG can also be used to make predictions about the outcome of future matches. By analyzing the xG of both teams, it is possible to get a sense of which team is more likely to win, draw, or lose the match. This can be useful for making betting decisions or for simply getting a better understanding of how a match is likely to play out.