AI correctly predicted the Albania win.
The match finished 0–3, validating the model's directional assessment.
Tracked markets vs full-time result
Prediction grade
B-
Each row compares the pre-match model lean to the full-time result.
- Market Prediction Result Outcome
- Over / Under 2.5 Over 2.5 Over 2.5 (3 goals) ✔ Correct
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Albania Albania ✔ Correct
- Correct Score Insights 1-1, 1-2, 2-1, 2-2, 1-3 0-3 ✖ Incorrect
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 3.79) — 3 goals materialised
- Over 2.5 goals aligned with the xG profile
What failed
- Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
- Exact score: outside the model's top score bins
Market lesson
The model's directional lean matched the full-time result (Albania win 0–3).
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Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 29, 2026 · 19:12 UTC Forecast generated
- xG · San Marino 1.81 — Albania 1.98
-
Sep 29, 2026 · 18:45 UTC Kickoff
-
FT Full-time result Albania win · 0–3
-
FT Prediction validated Directional lean matched full-time result
-
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
57/100
· Moderate
- Validation: Pending
Evidence
★★★★★
- Strong model lean
- Market has already priced much of the edge
- Validation pending
Market Compatibility
100/100
Betting Confidence
59/100
Validation Report
Immutable Snapshot
Closing Odds
Pending
AI Fair Odds
—
CLV
Pending
Final Result
Albania win · San Marino 0–3 Albania
Prediction
✔ Correct
Decision Grade
B-
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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UEFA Nations League — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | France | 4 | 3 | 1 | 0 | 10 |
| 2 | Italy | 4 | 2 | 1 | 1 | 7 |
| 3 | Belgium | 4 | 2 | 0 | 2 | 6 |
| 4 | Türkiye | 4 | 0 | 0 | 4 | 0 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Italy | 4 | 8 | 5 | +3 | 7 |
| 2 | France | 4 | 7 | 2 | +5 | 10 |
| 3 | Belgium | 4 | 6 | 5 | +1 | 6 |
| 4 | Türkiye | 4 | 2 | 11 | -9 | 0 |
| # | TEAM | MP | xG | xGC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | France | 4 | 2.0 | 0.6 | +1.4 | 10 |
| 2 | Italy | 4 | 2.0 | 1.4 | +0.6 | 7 |
| 3 | Türkiye | 4 | 1.4 | 2.0 | -0.6 | 0 |
| 4 | Belgium | 4 | 0.6 | 2.0 | -1.4 | 6 |
