Bet Check MVP

A dead-simple, high-signal sports betting companion for NBA bettors that shows real upcoming games, model predictions with confidence, and bookmaker odds side-by-side.

Features

• 📅 Upcoming NBA Games - Real-time games from ESPN
• 🤖 AI Predictions - Model predictions with confidence scores
• 📊 Odds Comparison - Current odds from major bookmakers
• 🎯 Value Detection - Find where model disagrees with market
• 💰 Affiliate Links - One-click path to place bets

Tech Stack

• Backend: FastAPI (Python) - /backend
• Frontend: Next.js 14 + Tailwind CSS - /frontend
• Data: ESPN API (games), The Odds API (odds)
• Deploy: Render.com ready

Quick Start

1. Backend Setup

cd backend
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

Create .env file:

cp ../.env.example .env
# Edit .env and add your ODDS_API_KEY from https://the-odds-api.com

Run backend:

python main.py
# Backend runs at http://localhost:8000

2. Frontend Setup

cd frontend
npm install
npm run dev
# Frontend runs at http://localhost:3000

3. Test

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

API Endpoints

Endpoint	Description
GET /health	Health check
GET /games	List upcoming NBA games
GET /predictions/{game_id}	Get prediction for a game
GET /game/{game_id}	Full game details with odds + prediction
GET /results/{game_id}	Game results
POST /webhook/stripe	Stripe webhook (skeleton)

Project Structure

bet-check/
├── backend/
│   ├── main.py          # FastAPI app
│   ├── db.py            # JSON file storage
│   ├── tests/
│   │   └── test_core.py # Pytest tests
│   └── requirements.txt # Python dependencies
├── frontend/
│   ├── pages/
│   │   ├── index.tsx         # Games list
│   │   └── game/[gameId].tsx # Game detail
│   ├── components/
│   │   ├── Header.tsx
│   │   ├── Card.tsx
│   │   └── ConfidenceMeter.tsx
│   └── styles/
│       └── globals.css
├── scripts/
│   ├── espn_fetcher.py  # ESPN API client
│   └── odds_fetcher.py  # Odds API client
├── render.yaml          # Render deployment config
└── .env.example         # Environment template

Deployment (Render.com)

1. Push to GitHub
2. Connect repo to Render.com
3. Create services from render.yaml or manually:
   • Backend: Python, build cd backend && pip install -r requirements.txt, start uvicorn main:app --host 0.0.0.0 --port $PORT
   • Frontend: Node, build cd frontend && npm install && npm run build, start npm run start
4. Add ODDS_API_KEY to environment variables
5. Done!

MVP Scope (v1)

• ✅ NBA only
• ✅ Real data from ESPN + The Odds API
• ✅ Mock predictions (improve later)
• ✅ No user accounts
• ✅ No auth/paywall
• ✅ DraftKings affiliate links

License

MIT

betcheck2

betcheck2

betcheck2.0