Bayer Leverkusen Data Analysis

This repository contains a Python notebook that analyzes Bayer Leverkusen's performance using open StatsBomb data. The notebook covers various aspects such as defensive and attacking performance, player statistics, and visualizations including radar plots and formation diagrams.

Overview

• Data Source:
  The analysis uses free datasets from StatsBomb (see StatsBomb Data).

• Notebook Highlights:

  • Defensive analysis and metrics (clearances, tackles, interceptions, blocks)
  • Attacking metrics and player performance
  • Visualization techniques like radar plots and pitch formations

Happy analyzing!

Setup Guide

1. Create a Virtual Environment
   Open your terminal and navigate to the project folder. Then run:

   python3 -m venv .venv

2. Activate the Virtual Environment

   • On macOS/Linux:

     source .venv/bin/activate

   • On Windows:

     .venv\Scripts\activate

3. Install Requirements
   Make sure you have a requirements.txt file. Then install the required packages:

   pip install -r requirements.txt

   If you encounter any problem, this is the list of the important packages to install:

   • statsbombpy
   • pandas
   • mplsoccer
   • flagpy
   • numpy
   • scikit-learn
   • matplotlib

4. Run the Notebook
   Launch Jupyter Notebook or JupyterLab:

   jupyter notebook

   or

   jupyter lab

   Open the BayerLev_DataAnalysis.ipynb notebook to start exploring the analysis.