Professional-grade arbitrage detection and bet optimization for NFL and NCAA Football, powered by advanced AI and autonomous agents.
Rabat combines sports betting arbitrage mathematics with enterprise-grade AI infrastructure to create an intelligent platform that:
- Detects arbitrage opportunities across multiple sportsbooks in real-time
- Predicts line movements using ML and historical pattern matching
- Optimizes bet allocation for guaranteed profit or maximum expected value
- Learns and improves automatically with autonomous intelligent agents
- Provides conversational insights through natural language AI
Built on the proven Incynt AI architecture (federated RAG, autonomous agents, intelligent caching) and adapted for sports betting.
- Multi-Book Arbitrage Detection: Find guaranteed profit opportunities across 7+ sportsbooks
- Advanced Opportunity Scoring:
- Margin Score (expected return %)
- Liquidity Score (bet limit assessment)
- Risk Score (volatility measurement)
- Closing Probability (time-to-close prediction)
- Optimal Bet Sizing: Risk-neutral allocation + Kelly Criterion
- Real-Time Odds Aggregation: Sub-60 second updates
- Historical Odds Database: Time-series storage for ML training
- Line Movement Prediction: ML models forecast closing lines
- Pattern Recognition: RAG system finds similar historical setups
- Market Intelligence Agent: Discovers new arbitrage patterns 24/7
- Opportunity Optimizer: Recommends optimal bet timing
- Data Quality Agent: Monitors odds integrity and staleness
- Conversational Interface: "Show me all NFL moneyline arbs over 3%"
- Apple-Style UI: shadcn/ui + Radix + Framer Motion
- Real-Time Dashboard: WebSocket push updates
- Interactive Charts: Heatmaps, line movement visualizations
- Dark Mode: Full theme support
- Mobile Responsive: Works on all devices
# Configure environment
cp backend/.env.example backend/.env
# Add your API keys: THE_ODDS_API_KEY, OPENAI_API_KEY
# Start infrastructure
docker-compose up -d
# Backend
cd backend
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload --port 8004
# Frontend (new terminal)
cd frontend
npm install && npm run devAccess: http://localhost:3004
from backend.sports.arbitrage_engine.core.arbitrage import ArbitrageDetector
arb = ArbitrageDetector.detect_two_way_arbitrage(
odds_side_a=Decimal("2.10"), # DraftKings
odds_side_b=Decimal("2.05"), # FanDuel
# ... game details ...
)
print(f"Margin: {arb.margin_score * 100:.2f}%") # 3.58%
arb = ArbitrageDetector.calculate_optimal_stakes(arb, Decimal("1000"))
print(f"Profit: ${arb.guaranteed_profit}")from backend.ai.rag_engine import RAGEngine
rag = RAGEngine()
similar = rag.search("Chiefs -3.5 moved to -6.5 before playoffs", top_k=5)python backend/cli.py chat
> "Show me NFL moneyline arbs over 3%"Run 24/7 to optimize the platform:
- Market Intelligence: Discovers arbitrage patterns
- Line Predictor: Forecasts closing lines
- Opportunity Optimizer: Finds optimal bet timing
- Data Quality Monitor: Validates odds integrity
# View dashboard
python backend/scripts/agent_monitor.py
# Deploy 24/7
./backend/scripts/deploy_agents.shBackend: Python 3.11, FastAPI, PostgreSQL, Redis, FAISS Frontend: Next.js 14, React 18, TypeScript, Tailwind, shadcn/ui AI: sentence-transformers, RAG, autonomous agents Infrastructure: Docker, Docker Compose
✅ Phase 1 (Current): Core arbitrage + AI infrastructure 🚧 Phase 2: ML predictions, smart parlays, alerts 🔮 Phase 3: Monte Carlo, social features, mobile apps
ARCHITECTURE.md- System designQUICKSTART.md- Setup guidePROJECT_STATUS.md- Feature statusINCYNT_INTEGRATION_PLAN.md- AI integration
Built with the proven Incynt AI architecture + custom sports betting expertise.
🚀 Find arbitrage opportunities with AI-powered intelligence.