AI correctly predicted the Al Thaid win.
The match finished 1–0, validating the model's directional assessment.
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 Over 2.5 Under 2.5 (1 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Al Thaid Al Thaid ✔ Correct
- Correct Score Insights 1-1, 1-0, 2-1, 0-1, 1-2 1-0 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Al Thaid | 41.8% | 54.7% | -12.9 pp | Market Higher |
| Draw | 25.7% | 24.3% | +1.4 pp | Aligned |
| Al Jazira Al Hamra | 32.6% | 21.0% | +11.5 pp | Model Edge |
The closing market estimates Al Thaid's win probability at 54.7%, compared with the model's estimate of 41.8%, a difference of 12.9 percentage points. This highlights a disagreement between the model and market consensus, without indicating which view is ultimately correct.
Model probabilities are generated from the statistical xG model using a Poisson distribution. Closing market probabilities are derived from consensus closing 1X2 odds after margin removal. Values represent implied probabilities rather than betting recommendations. Closing snapshot: PRE1.
After full time, the model's directional lean matched the result (Al Thaid win 1–0).
Market Assessment
The market is materially more optimistic about Al Thaid than the current fair estimate.
- Investors may be incorporating information not fully reflected in the baseline model.
- Tournament-specific context can shift market pricing.
Post Match Insights
What worked
- Exact score 1–0 fell within the model's highlighted bins
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 (1 goals)
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Al Thaid higher (54.7% vs model 41.8%, 12.9 pp), but the model's lean was validated (Al Thaid win 1–0).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Before kickoff Forecast generated
- Model 1X2 · Al Thaid 41.8% · Draw 25.7% · Al Jazira Al Hamra 32.6%
- xG · Al Thaid 1.45 — Al Jazira Al Hamra 1.25
-
May 03, 2026 · 13:50 UTC Opening odds snapshot PRE10
- 1X2 odds · Al Thaid 1.65 · Draw 3.72 · Al Jazira Al Hamra 4.29
- Implied 1X2 · Al Thaid 54.7% · Draw 24.3% · Al Jazira Al Hamra 21.0%
- Bookmaker · Pinnacle
-
May 03, 2026 · 13:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Al Thaid 1.65 · Draw 3.72 · Al Jazira Al Hamra 4.29
- Implied 1X2 · Al Thaid 54.7% · Draw 24.3% · Al Jazira Al Hamra 21.0%
- Bookmaker · Pinnacle
-
May 03, 2026 · 14:00 UTC Kickoff
-
FT Full-time result Al Thaid win · 1–0
-
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.
Pre-match metrics (historical context)
- Validation: Warning
- Large market gap (13 pp)
- No strong statistical edge
- Market has already priced much of the edge
- Validation warning
Validation Report
Immutable SnapshotModel 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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Division 1 — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Hatta SC | 28 | 18 | 5 | 5 | 59 |
| 2 | Dubai United | 28 | 17 | 7 | 4 | 58 |
| 3 | Al Urooba | 28 | 17 | 6 | 5 | 57 |
| 4 | Dibba Al Hisn | 28 | 17 | 5 | 6 | 56 |
| 5 | Al Arabi | 28 | 15 | 5 | 8 | 50 |
| 6 | Al Thaid | 28 | 13 | 9 | 6 | 48 |
| 7 | Emirates Club | 28 | 12 | 6 | 10 | 42 |
| 8 | Al Fujairah SC | 28 | 10 | 9 | 9 | 39 |
| 9 | Al Hamriyah | 28 | 10 | 8 | 10 | 38 |
| 10 | Gulf United | 28 | 7 | 4 | 17 | 25 |
| 11 | Al Jazira Al Hamra | 28 | 6 | 6 | 16 | 24 |
| 12 | Ittifaq | 28 | 7 | 3 | 18 | 24 |
| 13 | City | 28 | 6 | 5 | 17 | 23 |
| 14 | Al Dahra | 28 | 5 | 6 | 17 | 21 |
| 15 | Masfut | 28 | 5 | 6 | 17 | 21 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Dibba Al Hisn | 28 | 58 | 25 | +33 | 56 |
| 2 | Hatta SC | 28 | 57 | 25 | +32 | 59 |
| 3 | Al Fujairah SC | 28 | 46 | 47 | -1 | 39 |
| 4 | Dubai United | 28 | 45 | 28 | +17 | 58 |
| 5 | Al Hamriyah | 28 | 45 | 34 | +11 | 38 |
| 6 | Al Arabi | 28 | 44 | 34 | +10 | 50 |
| 7 | Gulf United | 28 | 39 | 52 | -13 | 25 |
| 8 | Al Urooba | 28 | 38 | 17 | +21 | 57 |
| 9 | Emirates Club | 28 | 38 | 39 | -1 | 42 |
| 10 | Al Thaid | 28 | 37 | 30 | +7 | 48 |
| 11 | Ittifaq | 28 | 37 | 57 | -20 | 24 |
| 12 | Al Jazira Al Hamra | 28 | 35 | 51 | -16 | 24 |
| 13 | Al Dahra | 28 | 30 | 56 | -26 | 21 |
| 14 | Masfut | 28 | 30 | 58 | -28 | 21 |
| 15 | City | 28 | 29 | 55 | -26 | 23 |
