The model missed the final outcome (Fulham win 3–1).
The model had projected Middlesbrough at 53.3%, but the full-time result went the other way.
Tracked markets vs full-time result
Each row compares the pre-match model lean to the full-time result.
- Market Prediction Result Outcome
- Over / Under 2.5 Under 2.5 Over 2.5 (4 goals) ✖ Incorrect
- Both Teams To Score BTTS No Yes ✖ Incorrect
- 1X2 Middlesbrough Fulham ✖ Incorrect
- Correct Score Insights 0-1, 1-1, 0-2, 1-2, 0-0 3-1 ✖ Incorrect
Post Match Insights
What failed
- Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (4 goals)
Market lesson
The full-time result was Fulham win 3–1, which did not match the model's pre-match lean on 1X2.
Prediction Timeline
How this prediction moved from forecast to full-time review.
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Before kickoff Forecast generated
- xG · Fulham 0.88 — Middlesbrough 1.56
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Jan 10, 2026 · 15:00 UTC Kickoff
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FT Full-time result Fulham win · 3–1
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FT Prediction missed 1X2 lean did not match full-time result
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Archived Prediction review
Historical Snapshot
Frozen at kickoff — the model output as it stood before the match started.
Pre-match metrics (historical context)
- Validation: Pending
- Moderate model lean
- Market has already priced much of the edge
- Validation pending
Validation Report
Immutable SnapshotProbability Calibration
- Expected: 53.3%
- Historical Bucket: 50–55% — Building sample
Model Performance
This prediction contributes to:
- Primary Bets ROI (180d): -100.0%
Review FAQ
- How accurate was the prediction?
- This page grades directional markets (1X2, Over/Under 2.5, BTTS) against the full-time result. The prediction grade reflects how many of those tracked markets matched reality.
- What does xG Accuracy measure?
- xG Accuracy compares the model's pre-match expected-goals profile to the actual scoreline — not whether every market hit. A strong directional review can coexist with a moderate xG accuracy score.
- Why wasn't the exact score predicted?
- Correct-score outcomes are low-probability tails even when the model reads the match profile well. We highlight top score bins for context; missing the exact line does not invalidate a directional review.
- Does this improve the AI record?
- Each finished match is logged in our validation pipeline. Aggregated hit rates and CLV studies are published separately — this page is the per-match audit trail.
Predictions are for informational purposes only. Always gamble responsibly and within your limits. Past performance does not guarantee future results.
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