AI correctly predicted the Bayern München win.
The match finished 2–0, validating the model's directional assessment.
Tracked markets vs full-time result
Prediction grade
F
Each row compares the pre-match model lean to the full-time result.
- Market Prediction Result Outcome
- Over / Under 2.5 Over 2.5 Under 2.5 (2 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Bayern München Bayern München ✔ Correct
- Correct Score Insights 2-1, 1-1, 2-2, 3-1, 1-2 2-0 ✖ Incorrect
Post Match Insights
What worked
- Bayern München attacking xG significantly stronger (2.30 vs 1.56)
What failed
- Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
- Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)
Market lesson
The model's directional lean matched the full-time result (Bayern München win 2–0).
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Prediction Timeline
How this prediction moved from forecast to full-time review.
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Before kickoff Forecast generated
- xG · Bayern München 2.30 — RB Leipzig 1.56
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Feb 11, 2026 · 19:45 UTC Kickoff
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FT Full-time result Bayern München win · 2–0
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FT Prediction validated Directional lean matched 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.
Historical verdict:
Observe
Historical Decision
No Primary Bet
Outcome
Validated
Pre-match metrics (historical context)
Prediction Reliability
51/100
· Moderate
- Validation: Pending
- High xG deviation from league baseline (70%+)
Evidence
★★★★★
- Moderate model lean
- Market has already priced much of the edge
- Validation pending
Market Compatibility
100/100
Betting Confidence
53/100
Validation Report
Closing Odds
Pending
AI Fair Odds
—
CLV
Pending
Final Result
Bayern München win · Bayern München 2–0 RB Leipzig
Prediction
✔ Correct
Decision Grade
F
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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