Point-in-time evidence
Official schedules, game context, lineups, injuries, market state when available, and source timestamps are captured before the event—not reconstructed after it.
ABOUT TORK BROSSports intelligence
Sports intelligence
that has to prove itself.
TORK BROS turns point-in-time sports evidence, four separately recorded model opinions, and one accountable house decision into an immutable record that can be audited after the result.
Not another scoreboard. Not another picks feed.
The product is an accountability system for sports decisions. Users can see the live score quickly. The deeper value is knowing what was forecast, when it was locked, why the house acted or abstained, and how that decision performed.
4 separate model reports1 TORK BROS decisionTracked coverage and exclusions
One continuous decision-and-audit system
Each layer creates a record the next layer can verify.
Separate model reports
ChatGPT, Claude, Grok, and Gemini analyze the same matchup in separate calls. Their completed outputs remain separate, attributable, and comparable.
TORK BROS adjudication
A distinct house layer records one PICK, LEAN, PASS, or WITHHELD decision. It does not masquerade as a fifth model.
Immutable pregame lock
Eligible forecasts, inputs, model versions, probabilities, and decision timestamps are locked before play begins.
Official result audit
The platform connects each eligible lock to the official result and grades the house decision and every participating model.
Calibration memory
Accuracy, Brier score, log loss, disagreement, abstention, and data quality become a growing sport-specific evidence record.
A growing evidence asset. A competitive advantage still to prove.
The time-stamped record supports forecast comparison and reliability tests. Its commercial value depends on data quality, measurable benefits, and customer demand. Collection size alone does not prove a moat.
A synchronized evidence record
The potential asset is the time-aligned record of available evidence, model outputs, and decisions before each outcome. Its usefulness must be tested.
Disagreement becomes labeled data
We preserve where models agree, split, or fail to report—then connect those patterns to house decisions and official outcomes. Over time, those disagreement signatures become measurable.
Abstention is part of the product
PASS and WITHHELD are first-class decisions. The system learns where evidence is incomplete or conflicting instead of forcing a prediction into every market.
Cross-sport controls, sport-specific proof
MLB and MMA share the audit architecture, but keep separate validation records, evidence rules, and promotion thresholds. One sport cannot borrow credibility from another.
Evidence→Model disagreement→House decision→Official outcome→Calibration
We do not claim an edge before it is demonstrated.
Follow the registered 600-pair, 60-date market test →
Current LEAN, PASS, and WITHHELD outputs are research forecasts during shadow validation. Only eligible, pre-event locked decisions enter the prospective record. Historical backtests remain separate.
WHY IT COMPOUNDS
Measure what each new record adds.
The growing corpus connects evidence quality, model provenance, probability ranges, disagreement, house adjudication, abstention, and official outcomes. That enables sport-specific calibration, reliability analysis, and better decision controls—without rewriting history.