The real money in the sports industry is right in front of us—billions of dollars circulate globally every year, with major events like the NFL taking the lion's share. The problem is that most of these profits are eaten up by traditional intermediaries, with sky-high fees, opaque rules, and many countries and regions lacking legal channels to participate.

On-chain prediction markets initially seemed like a perfect substitute: decentralization means no one can arbitrarily change the rules, transparency is inherent, and users worldwide are not restricted by geography. However, this sector has been stuck on a critical issue—where does the sports data come from?

Recently, there has been a breakthrough. A certain oracle platform announced the official integration of NFL data. This may seem like a minor update, but for the on-chain prediction market ecosystem, it marks a watershed. Developers can finally access reliable, verifiable, near real-time data sources, no longer relying blindly on centralized APIs or manual verification methods. The overall trust and user experience of the market can now reach a new level.

What’s interesting is how this platform handles sports data. NFL game information is scattered everywhere—official statements, ESPN reports, social media discussions, live broadcasts. These sources come in various formats: HTML pages, PDFs, video footage, tweets.

That’s the core issue. Traditional oracle technology simply cannot handle such complex scenarios; it only reads structured data—like numbers and fixed-format JSON. It fails when faced with PDFs or videos. The new generation of solutions is equipped with an AI ingestion layer, specifically using OCR to recognize images and videos, combined with natural language processing to understand unstructured information. This makes previously impossible tasks feasible.