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Expected-Goals

I have used wyscout data to create a xG model. The expected goal values can be used to draw inferences about the performances of individual players as well as to analyze the performance of teams in matches.

  1. Preprocess - contains a function to extract the information relevant for creating an expected goals model from the dataset.
  2. xG model - comparing different classification algorithms to find the best fit.
  3. Goalscorers - Using the predicted xG values to look for the best goalscorers of the 2017-2018 season in the top-5 leagues (open play goals).
  4. xG-Rolling- Creating rolling xG charts for matches to better understand how the match panned out for different teams.
  5. Shotmaps- Shot maps of different players as well as for a particular game played.

Dataset

The dataset used is taken from the paper, https://www.nature.com/articles/s41597-019-0247-7. Further documentation for the same can be found here- https://apidocs.wyscout.com/#section/Versioning/Version-Switch

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Using wyscout data to create a xG model

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