AI Sports Odds Comparator

I’m building a responsive web app that runs smoothly on any iPhone browser and on Windows desktops. Its core purpose is to pull live H2H, line, and total-points markets for NRL, AFL, NBL, MLB, NBA, NFL, and NHL, then compare the numbers from Tab, Betfair, Sportsbet, Ladbrokes, Tabbtouch, Pointsbet, and Pickle Bet against an AI-driven “fair price”. I do have an api for sports [login to view URL] But will still need to get players in and out js weather and that from some where. The interface must follow a modern, minimalistic aesthetic: clean typography, quick filters, and an uncluttered dashboard that immediately highlights value gaps. Behind the scenes, the app needs a real-time data pipeline that keeps bookmaker odds, player ins-and-outs, and venue weather in sync so the model can recalculate probabilities the moment something changes. I’m after in-depth analysis, not just a green/red value light. Each game should display: • the model’s implied win probability and recommended price • projected line and expected total points • percentage edge versus every bookmaker on screen A quick-view of key weather metrics (temperature, wind, rain) and confirmed line-ups must sit beside each matchup so users see the factors the model has incorporated. Deliverables 1. Full source code for the web app, responsive on iOS Safari and Windows Chrome/Edge 2. Live demo URL or test flight build demonstrating sub-5-second odds refresh and sub-60-second player/weather updates 3. Documented data sources, model methodology, and environment setup instructions 4. Admin panel for adding new bookmakers or tweaking model parameters 5. Automated tests covering data ingestion, model outputs, and UI critical paths I’m flexible on the final tech stack—React or Vue on the front end, Python (TensorFlow, PyTorch, or XGBoost) or a Node alternative for the AI layer are all fine as long as they deliver speed and transparency. Let me know how you’d structure the data feeds, what modelling approach you would use, and any previous work that proves you can bring real-time sports analytics to life.

Project ID: 40571124