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fpl-analysis

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Repository designed to work with data from the Premier League. It is used as both a personal self-study as well as a tool to fetch, analyze and model performance metrics to maximize returns in a returns-based game called Fantasy Premier League (FPL).

  • Updated Dec 9, 2024
  • Python

Integrating FPL, Transfermarkt, and Understat data, our strategy optimizes squad selection. This approach, leveraging market values and detailed player statistics, ensures both financial prudence and on-field performance. Strategic acquisitions align with set rules and budget constraints, emphasizing value-driven choices for a robust squad

  • Updated Feb 4, 2024
  • Jupyter Notebook

Predict Fantasy Premier League (FPL) points using two models: a Random Forest regression (ML_xP.py) and a custom statistical model (xP_FPL.py). This project explores different approaches to predicting player performance, with a detailed comparison for Gameweek 5 of the 2024/25 EPL season.

  • Updated Oct 30, 2024
  • Python

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