EdgePredict
A rules-based sports market intelligence system comparing Kalshi pricing against sportsbook consensus, estimating positive EV with hard risk controls before any action is allowed — an exploration of how data and automation apply to sports markets.
Background / Architecture
What this system proves
Note
Built a public-facing React and Vite demo that explains a sports prediction-market engine in plain English while packaging the system cleanly for portfolio review.
Note
Designed the core workflow around market scanning, fair-probability estimation, EV evaluation, liquidity checks, duplicate-position prevention, and server-side execution safeguards.
Note
Showcases disciplined product thinking for automation and finance: explainable decisioning, conservative risk rules, and a private cloud-backed system instead of black-box betting picks.