Sire & Score: Where AI meets Prediction Markets

Introduction

Sports betting remains one of the world’s largest and most enduring markets. Valued at over $100B in 2024, the industry is projected to grow 11% annually through 2030. Yet it still runs on infrastructure that looks more like a casino than a financial market: opaque, state-regulated, and inefficient. A new wave of prediction markets is beginning to change that, blurring the line between gambling and investing by turning sports outcomes into tradeable assets where odds move dynamically like prices on an exchange.

As these markets evolve, the ability to spot mispricings and inefficiencies across odds becomes the next source of tradable edge. Sire and Score embody this shift, a new model for quantitative sports trading built on decentralized AI. Sire is the first customer of Score, a Bittensor subnet that uses advanced AI to analyze videos. It is the perfect early use case, showing how the technology turns sports gameplay footage into actionable trading intelligence. After the recent crypto market meltdown, demand for products that offer diversified, non-market-correlated exposure is likely to accelerate, with Sire and Score positioned squarely at the center of that opportunity.

Prediction Markets See Growing Demand for Sports

Prediction markets are experiencing a surge in activity, with sports contracts rapidly becoming their dominant category. While political events initially drove most of the traction ahead of the November U.S. presidential elections, sports markets have since taken the lead, accounting for 50% to 70% of total volumes on Polymarket for most weeks.

The same trend is evident on Kalshi, where sports-related categories now represent 85% of weekly volumes. Last week alone, Kalshi processed $877M in sports market volumes, underscoring the vast addressable opportunity for Sire and Score.