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World Cup Data Visualization

  • Used different statistical approaches and other data processing and data visualization techniques to analyze player or teams performances through various sorts of events; passes, carries, shoots, defensive actions, and so on, using statsbomb free event data, specifically World Cup 2022 event data.
  • Preprocessed and extracted aggregated data (metrics) of player's performance throughout the whoel comptition and profiled these players.

Plots

  • Ball carrying distribution by player.
  • A player's carries that ended in the opponent's half.
  • Calculated the truer progressing carrier and plotted all of their carries.

  • Demonstrated a player's two-footedness by plotting his right and left foot passes.
  • Passing Networks.
  • Hetmaps displaying where forwards from national African teams received the ball.
  • Goalkicks Analysis:

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  • Passes pitch plot: included passes, progressive passes, key passes, assists, and passing completion rate.
  • Carries pitch plot: included carries, progressive carries, attempted dribbles, and succesful dribbles.
  • Defensive actions pitch plot: includes attempted and won tackles, interceptions, ball reoveries, and aerials (attempted & won).
  • Putting all this plots together we get to visualize a player performances through different aspects of the game:

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  • I extracted aggregated data and analyzed a midfielder using a set of on-ball metrics:

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  • Shots taken by players, supported with number of shots, goals, xG (expected goals) and xG per shot
  • Shots taken during a match

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About

Visualization of the World Cup's 22 event data. In this project I aim to extract insights regarding player and national team performances in Quatar.

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