NBA Fantasy Basketball Prediction Platform

This is a monorepo for a full-stack NBA fantasy basketball analytics and prediction platform. It features a React/TypeScript frontend and a FastAPI/Python backend, supporting advanced machine learning models for player projections, custom fantasy scoring, and interactive analytics.

Project Structure

Project-Mono-Repo/
├── backend/      # FastAPI backend, ML models, and data
│   ├── api_service.py
│   ├── CSVs/                # Player, boxscore, and model data (CSV)
│   ├── Models/              # Pre-trained (pre-trained models)
│   ├── Output/              # Model prediction CSVs
│   ├── TrainingAndTesting/  # Jupyter notebooks for ML models
│   ├── requirements.txt
│   └── README.md            # Backend-specific setup & docs
├── frontend/     # React + TypeScript + Tailwind CSS dashboard
│   ├── src/
│   ├── package.json
│   └── README.md            # Frontend-specific setup & docs
├── ploty-dash-frontend/     # (Optional) Plotly Dash analytics (Python)
├── README.md                # (This file) Project overview & quick start

Requirements

• Python 3.8+
• Node.js 18+
• npm
• (Recommended) virtualenv or conda for Python

Quick Start

1. Backend (FastAPI)

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn api_service:app --reload --port 8001

The API will be available at http://localhost:8001

2. Frontend (React)

cd frontend
npm install
npm run dev

The dashboard will be available at http://localhost:5173

Folder Details

• backend/: All Python code, data, and ML models. See backend/README.md for details.
• frontend/: All React/TypeScript code for the dashboard. See frontend/README.md for details.
• ploty-dash-frontend/: (Optional) Python Plotly Dash analytics app.

Data & Models

• Place all CSV data in backend/CSVs/.
• Place all model prediction CSVs in backend/Output/.
• See backend/README.md for details on supported files and formats.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes and test
4. Submit a pull request

License

MIT

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See backend/README.md and frontend/README.md for detailed setup, usage, and development instructions for each part of the project.