EdgePredict
A live GitHub Pages demo for a rules-based sports market intelligence system that compares Kalshi pricing against sportsbook consensus, estimates positive EV, and applies hard risk controls before any action is allowed.
Background / Architecture
What this system proves
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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.
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Designed the core workflow around market scanning, fair-probability estimation, EV evaluation, liquidity checks, duplicate-position prevention, and server-side execution safeguards.
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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.