NFL Calibration and Backtesting

PATTERN PICKS · MODEL VALIDATION

NFL Calibration & Backtesting

Transparent validation of recorded pregame research, independent final-score verification and future model calibration. No claimed edge without sufficient out-of-sample results.

Market Intelligence · Results Audit · Bet Tracker

Forward Test — Verification Status

Live counts come from the pregame research ledger. Predictions remain ungraded until independently verified final scores are available. No win rate or betting edge is inferred from pending games.

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Open timestamped pregame ledger → · View score verification audit →

Live verified grading dashboard

Verified Forward Research Results

As of 2026-10-21T10:50:49+00:00 (UTC) · Source verified: 2026-10-21T07:34:50+00:00 (UTC) · Cached up to 5 minutes

Recorded research snapshots194
Independently graded15
Correct5
Incorrect10
Awaiting verified final0
Not yet played179
No selection0
Invalid snapshots0
Forward accuracy33.3% (15 graded)

Research selections are not recorded wagers. Final-score verification does not verify sportsbook odds, player props, settlement, or ROI. Small samples are not evidence of predictive edge.

Verification-to-Grading Pipeline

Follow each stage from a saved pregame forecast to an independently confirmed final result. A pending final cannot become a win or loss merely because a score was imported.

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Counts represent different stages and may not be directly comparable: verification counts cover imported game records, while grading counts cover eligible recorded forecasts. This panel does not modify backend verification or force grading.

Validation methodology

  1. Freeze predictions: preserve the model version, timestamp, teams and selection before kickoff.
  2. Independently verify outcomes: use final-score records with traceable sources; separately verify player statistics for props.
  3. Use chronological holdouts: train only on information available before each game and evaluate on later unseen games.
  4. Calibrate probabilities: report reliability by predicted-probability bucket, Brier score, log loss and uncertainty intervals only after enough valid samples.
  5. Compare against markets: capture bookmaker, identical market/line, price and observation time. Remove vig for a fair market benchmark and avoid treating price differences alone as an edge.
  6. Report honestly: publish counts, exclusions, pushes, voids and confidence intervals. Keep model forecasts distinct from actual wager performance.

Research resources

Existing Model Backtest · Pregame Ledger · Live NFL Odds · NFL Player Props

Disclosure: No forward win rate, profitable expected value or player-prop prediction accuracy is currently established by the independently graded dataset.