A Streamlit dashboard for analyzing Premier League team performance with match-level statistics from FotMob.

• Season Overview: Points, wins, draws, losses, cumulative points chart, home/away splits, recent form
• Attacking Analysis: Goals, xG, shots, big chances, shot quality metrics, tactical insights
• Defensive Analysis: Goals conceded, tackles, interceptions, clean sheets, defensive actions
• Possession & Passing: Ball possession, pass accuracy, long balls, crosses, touches in box
• Match Explorer: Browse individual match statistics

# Clone the repository
git clone https://github.com/yourusername/pl_team_analysis.git
cd pl_team_analysis

# Install dependencies
pip install -r requirements.txt

# Run the dashboard
streamlit run app.py

pl_team_analysis/
├── app.py                    # Main Streamlit entry point
├── config.py                 # Configuration (paths, defaults)
├── requirements.txt          # Python dependencies
├── datasets/                 # CSV data files
│   ├── fotmob_season_2023-2024_stats.csv
│   └── fotmob_season_2024-2025_stats.csv
├── src/
│   ├── data/
│   │   ├── loader.py         # Data loading with caching
│   │   └── preprocessor.py   # Data cleaning & transformation
│   ├── metrics/
│   │   ├── attacking.py      # Goals, xG, shots metrics
│   │   ├── defensive.py      # Tackles, clean sheets metrics
│   │   ├── possession.py     # Possession, passing metrics
│   │   └── aggregators.py    # Season summaries, form
│   ├── visualizations/
│   │   ├── charts.py         # Plotly chart functions
│   │   └── theme.py          # Team colors, styling
│   └── utils/
│       └── constants.py      # Team names
└── pages/                    # Streamlit multi-page app
    ├── 1_Season_Overview.py
    ├── 2_Attacking_Analysis.py
    ├── 3_Defensive_Analysis.py
    ├── 4_Possession_Passing.py
    └── 5_Match_Explorer.py

Match statistics scraped from FotMob using my fotmob-scraper.

Included seasons:

• 2023-2024 Premier League season
• 2024-2025 Premier League season

You can add more seasons or leagues by following these steps:

1. Scrape data using fotmob-scraper

2. Add CSV file to the datasets/ folder:

   datasets/
   ├── fotmob_season_2023-2024_stats.csv
   ├── fotmob_season_2024-2025_stats.csv
   └── fotmob_season_2025-2026_stats.csv  # Your new file
   

3. Update config.py to include the new season:

   SEASON_FILES = {
       "2023-2024": DATASETS_DIR / "fotmob_season_2023-2024_stats.csv",
       "2024-2025": DATASETS_DIR / "fotmob_season_2024-2025_stats.csv",
       "2025-2026": DATASETS_DIR / "fotmob_season_2025-2026_stats.csv",  # Add this
   }
   
   # Optionally update default season
   DEFAULT_SEASON = "2025-2026"

4. Restart the app and the new season will appear in the dropdown

• Frontend: Streamlit
• Data Processing: Pandas, NumPy
• Visualization: Plotly

MIT License - feel free to use this project for your own analysis.

Contributions are welcome! Feel free to open issues or submit pull requests.