GaitSignal

Live football pricing-edge concept demo using player-specific movement surprise and venue-grade tracking for in-play market information.

GaitSignal is a synthetic React prototype demonstrating how contracted in-stadium player tracking combined with player-specific movement models could surface in-play pricing edges before standard market digestion. The core thesis: per-player temporal models with prediction-surprise scoring, gated by football context (possession, ball access, pitch zone, role demand), reveal commercially relevant signals that universal thresholds miss.

This is a concept demo – the companion piece to Acoustic Momentum. One modality from the player, one from the crowd. Both explore in-play information that the market may not yet fully price.

Key Features

• Player-specific movement surprise scoring with football context gating
• Synthetic biomechanical vector generation for three match scenarios (Saka recovery-run reprice, Pedri press-decay edge, Musiala contact reset)
• Trading desk UI with match state, player motion lens, pricing workflow timeline, and in-play pricing edge panels
• Football-native workflow – venue-grade data assumption, not reskinned basketball analytics
• Companion concept to Acoustic Momentum for multi-modal pricing edge exploration

Technical Architecture

The demo generates synthetic 20-feature biomechanical vectors, player-specific movement-surprise proxies, and venue-style football context streams. The UI is built in React with TypeScript, using D3.js and Recharts for visualization. It is organized like a live trading desk – multiple coordinated panels showing match state, individual player motion analysis, pricing workflow progression, and edge state indicators.

Three built-in scenarios demonstrate different signal patterns: a recovery-run reprice event, a press-decay edge, and a contact reset. Each scenario shows how the same pipeline produces different actionable signals depending on player role, pitch zone, and match context.