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It can also predict the market value of individual players using trained machine learning models.\n\n---\n\n## Project Structure\n\n- `app.py` - Main Streamlit app.\n- `trainTeam.py` - Script to train the team recommendation model.\n- `trainMarket.py` - Script to train the player market value prediction model.\n- `data.csv` - Dataset with player information.\n- Model pickle files (`market_value_model.pkl`, `label_encoders.pkl`, etc.) generated after training.\n\n---\n\n## Setup Instructions\n\n### Prerequisites\n\n- Python 3.7 or higher\n- pip (Python package installer)\n\n### Installation\n\n1. Clone or download the project files to your local machine.\n2. Navigate to the project directory in your terminal or command prompt.\n3. (Optional but recommended) Create and activate a virtual environment:\n\n   ```bash\n   python -m venv venv\n   # Windows\n   venv\\Scripts\\activate\n   # macOS/Linux\n   source venv/bin/activate\n   ```\n\n4. Install required Python packages:\n\n   ```bash\n   pip install streamlit pandas plotly scikit-learn numpy\n   ```\n\n5. Ensure `data.csv` is present in the project folder.\n6. Run training scripts to generate the necessary model files:\n\n   ```bash\n   python trainMarket.py\n   python trainTeam.py\n   ```\n\n---\n\n## Running the Application\n\nStart the Streamlit app by running:\n\n```bash\nstreamlit run app.py\n```\n\nThis will launch the app in your default web browser, usually at `http://localhost:8501`.\n\n---\n\n## How to Use\n\n### Options\n\n- **Recommend a Team:**  \n  Enter your budget, select a formation (4-3-3, 4-4-2, or 3-4-3), and choose a playing style (Attacking, Balanced, Defensive). Click \"Generate Team\" to see a recommended lineup and a visual formation on the field.\n\n- **Predict Player Market Value:**  \n  Select a player from the dropdown list and click \"Predict\" to see an estimated market value and a radar chart showing key player stats.\n\n---\n\n## Notes \u0026 Troubleshooting\n\n- Ensure `data.csv` is complete and correctly formatted.\n- If you encounter errors about missing model files, re-run the training scripts.\n- Plotly visualizations require a functional browser.\n- Use a virtual environment to avoid dependency conflicts.\n\n---\n\n## Contact\n\nFeel free to reach out if you have questions or need assistance.\n\n---\n\nEnjoy building your SmartXI football team! ⚽","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabtaaahi%2Fsmartxi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabtaaahi%2Fsmartxi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabtaaahi%2Fsmartxi/lists"}