Big 5 European Football Leagues Dashboard

📊 Project Overview

This Streamlit dashboard provides a comprehensive analysis of the top 5 European football leagues for the 2023/24 season. It offers insights into team performances, top scorers, and in-depth statistics across the Premier League, La Liga, Bundesliga, Serie A, and Ligue 1.

🌟 Features

• League Table: View the current standings for each league.
• Top Scorers: Explore the leading goal scorers in each country.
• Team Analysis:
  • Detailed performance metrics for each team.
  • Radar charts for visual performance comparison.
  • Expected vs. Actual Goals Analysis.
  • Form analysis with win-draw-loss distribution.
• League-wide Analysis:
  • Points vs. Expected Points scatter plot.
  • Attendance vs. Performance visualization.
  • Performance Efficiency Analysis across leagues.
• Interactive Filters: Select specific countries or teams for detailed analysis.
• Responsive Design: Optimized for both desktop and mobile viewing.

🛠️ Technologies Used

• Python
• Streamlit
• Pandas
• NumPy
• Plotly
• SciPy

📦 Installation

1. Clone this repository:

   git clone https://github.com/your-username/big5-football-dashboard.git
   

2. Navigate to the project directory:

   cd big5-football-dashboard
   

3. Install the required packages:

   pip install -r requirements.txt
   

🚀 Usage

1. Ensure you have the data file data.csv in the data/ directory.

2. Run the Streamlit app:

   streamlit run app.py
   

3. Open your web browser and go to http://localhost:8501 to view the dashboard.

📁 Project Structure

big5-football-dashboard/
│
├── app.py                 # Main Streamlit application
├── data/
│   └── data.csv           # Dataset file
├── requirements.txt       # Python dependencies
├── README.md              # This file
└── .gitignore             # Git ignore file

📊 Data Source

The data used in this dashboard is sourced from FBREF. Last updated: 2024-07-08.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page if you want to contribute.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

Dennis Seroney

• Website: analyticske.github.io
• GitHub: @analyticske

🙏 Acknowledgements

• Data provided by FBREF
• Built with Streamlit
• Visualizations powered by Plotly

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