Cadangan: Standard Pengesahan Terbuka untuk AI Sukan

The Problem

The sports AI industry has no shared standard for what "verified" means. Every platform defines accuracy differently, measures performance inconsistently, and reports results selectively.

This makes it impossible for users, builders, or institutions to compare outputs across platforms.

Our Proposal

We're publishing a draft specification for an Open Verification Standard (OVS) that defines:

1. Signal Schema A standardized JSON schema for sports intelligence signals, including required fields for confidence scoring, agent attribution, and data source provenance.

2. Audit Trail Format A standardized format for post-match verification logs, enabling third-party auditing of any platform's claimed accuracy.

3. Consensus Reporting A framework for reporting multi-agent consensus metrics, distinguishing between single-model confidence and cross-agent agreement.

4. Performance Metrics Standardized definitions for accuracy, precision, recall, and calibration in the context of sports intelligence.

Why This Matters

An open standard benefits the entire ecosystem: - Users can compare platforms objectively - Builders can create cross-platform tools - Institutions can set procurement standards - Regulators can establish compliance frameworks

Next Steps

The draft specification is available for public comment. We welcome feedback from builders, institutions, and competing platforms. A rising tide lifts all boats — and the tide here is trust.