The measure of expected goals in a a football game is discussed in the work. The concept and calculation of expected goals is presented both theoretically and practically. The impact of the distribution of expected goals and their use to quantify player or team performance is described. On the basis of expected goals, the measure of expected points is derived and practically presented. A method for predicting the results of football games based on the Poisson distribution is presented and updated to take expected goals into account. A practical example compares methods with and without taking expected goals into account.
The topic under discussion is currently rapidly developing. Most of the ideas are obtained in semi-professional articles online. In the present work, they are translated into mathematical or statistical language and presented in an orderly and comprehensive manner, and some new ideas of the author are also added. Practical examples are added to all theoretically presented concepts.
All analyses, simulations and results are obtained with the help of the computer statistical program R. As part of this, some specific packages are used, such as regista, StatsBombR, ggsoccer, SBpitch, worldfootballR and soccermatics.
The approach used has proven to be effective. We assessed which variables statistically significant and in what way affect the probability of a goal in a football game at the highest male professional level. In the future, it would be reasonable to extend the analyzes to the study of factors that influence the variables from which the xG value is calculated. We could look at how the xG values vary between different levels of competition. We could also predict the results of football games with some machine learning models and check the impact of the inclusion of the xG value on the quality of the predictions.
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