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Messi Data’s Playbook: Optimizing Lineups and Substitutions with AI

Team Messi Data: John He, Daeun Ji, Teddy Debreu, and Kavya Bhat

Purpose

This project focuses on analyzing soccer match data and developing an AI-powered lineup recommendation and substitution system.


File Structure

  • README.md # Project description and guide
  • requirements.txt # List of required packages for the project
  • extract_data_from_pdfs.ipynb # Jupyter Notebook for extracting data from PDFs
  • extract_player_data.ipynb # Jupyter Notebook for analyzing player data
  • initial_lineup_generator.py # Python script for generating initial lineups
  • Player_Substitution.ipynb # Jypyter Notebook for analysing substition player

How to use our code

Clone Repository

  • Clone our repository into a folder. You will be working within this folder.

Data Location

Virtual Environment Set Up

You will need to have python3 and anaconda installed. If these are not installed, please install them.

Open Terminal and run the commands below to install the correct packages to run our code

conda create -n hackathon2024env

conda activate hackathon2024env

conda install pip

pip install -r requirements.txt

Generate cleaned data

  • Open extract_data_from_pdfs.ipynb and run all code chunks
  • Open extract_player_data.ipynb and run all code chunks

Run ML models

  • Open and run (or run in terminal) initial_lineup_generator.py
  • Open Player_Substitution.ipynb and run all code chunks

Run AI Chat Bot

  • Make sure you are in our directory.
  • Get OpenAI API Key for GPT 4o-mini.
  • ON MAC-Open terminal and write this command: export OPENAI_API_KEY="your-key-here"
  • ON PC-Open Powershell and write this command: $ENV:OPENAI_API_KEY="your-key-here"
  • Run Command: python tedlasso.py in terminal

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