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Building xG and xGOT based on Statsbomb World Cup 2022 Open Data

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Building xG and xGOT based on Statsbomb World Cup 2022 Open Data

This repo contains my Notebook that covers steps to build simple expected goals (xG) model and expected goals-on-target (xGOT) model.

xG Model

First, I built a simple model with only 2 features that are angle and distance of the shot. Then, I built the 2nd model with more features that are:

  • Shot types of play (penalty, free kick)
  • Body part (header, preferable side)
  • Is under pressure?
  • Shot technique

I also identified which team is the biggest overachiever and underachiever.

xGOT Model

I built the xGOT model with just simple features that are the distances of the end shot to the center of goal. I also visualized players to see how their xG and xGOT correlated to each other, made us know which player has better chances and which player has better shot placing ability.

Articles

I wrote two articles regarding this project

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Building xG and xGOT based on Statsbomb World Cup 2022 Open Data

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