Expected goals model — Football Analytics

Expected goals is a statistical model used to estimate the likelihood of a shot resulting in a goal. It is based on a range of variables that can affect the outcome of a shot, such as the location of the shot, the angle of the shot, the type of pass that led to the shot, and the presence of defenders.

The expected goals model assigns a value, or expected goal value, to each shot based on the probability of it resulting in a goal. This value is typically expressed as a decimal between 0 and 1, with higher values indicating a higher probability of the shot resulting in a goal.

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Expected goals is a statistic that was developed by a group of statisticians and soccer analysts as a way to quantify the quality of chances that teams and players create and concede in soccer matches. While the specific details of how expected goals are calculated may vary, the concept of using data to estimate the likelihood of a particular shot resulting in a goal has been around for some time.

One of the earliest versions of expected goals was developed by David Sumpter, a professor of applied mathematics at the University of Uppsala in Sweden, and his colleagues in the mid-2000s. Sumpter and his team used data from thousands of soccer matches to develop a model that could predict the likelihood of a shot resulting in a goal based on the location of the shot, the type of pass or dribble that led up to the shot, and the type of shot taken.

Since then, expected goals has become an increasingly popular statistic in the soccer analytics community and is used by a wide range of analysts, teams, and media outlets to evaluate and analyze the performance of teams and players.

Why are expected goals important?

• They often tell a story about a match or recent matches, e.g. sometimes, the better playing team doesn’t win the game.
• They predict future goals better than the actual goals.
• They can be used to help guide players and coaches in decision making.
• They are the first step in an approach to football data that is grounded in a model.

The expected goals model can be used to evaluate the performance of individual players, teams, or entire leagues. It can be used to identify areas for improvement and to make more informed decisions about tactics and player selection.

Expected goals has become an increasingly popular tool in the analysis of football (soccer) and is used by many professional clubs and media outlets as a way to evaluate the quality of chances being created and conceded. It is not, however, a perfect model and should be used in conjunction with other statistical and subjective analysis.

In soccer, expected goals can be used to provide a more accurate assessment of a team’s or player’s attacking performance. For example, a team that consistently generates high-quality chances but fails to convert them may be performing better than its actual goal total suggests. On the other hand, a team that scores a lot of goals but does so from low-quality chances may be overperforming and could be expected to see a dip in its goal-scoring rate in the future.

Expected goals can also be useful for analyzing defensive performance. For example, a team that allows a high number of shots but has a low expected goals against may be performing better than its goals against total suggests, as it may be preventing opponents from taking high-quality shots.

In addition to being a valuable tool for analyzing and evaluating team and player performance, expected goals can also be used to make more informed predictions about future matches. By taking into account the quality of chances a team or player is creating and conceding, expected goals can provide a more accurate assessment of a team’s or player’s likely performance in future matches.

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