AI correctly predicted the Al Minaa Basra win.
The match finished 3–0, 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 Under 2.5 Over 2.5 (3 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Al Minaa Basra Al Minaa Basra ✔ Correct
- Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-0 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Al Minaa Basra | 37.5% | 42.5% | -5.0 pp | Aligned |
| Draw | 29.6% | 33.4% | -3.8 pp | Aligned |
| Gharraf | 32.9% | 24.1% | +8.8 pp | Model Higher |
The statistical model estimates Gharraf's win probability at 32.9%, compared with the closing market's implied probability of 24.1%, a difference of 8.8 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 Minaa Basra win 3–0).
Market Assessment
The fair estimate shows a modest edge over current market pricing on Gharraf.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
What failed
- Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Al Minaa Basra more conservatively (28.7% vs model 37.5%, 8.8 pp), but the model's lean was validated (Al Minaa Basra win 3–0).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 26, 2026 · 17:59 UTC Forecast generated
- Model 1X2 · Al Minaa Basra 37.6% · Draw 29.6% · Gharraf 32.9%
- xG · Al Minaa Basra 1.35 — Gharraf 1.25
-
Aug 26, 2026 · 17:31 UTC Opening odds snapshot PRE30
- 1X2 odds · Al Minaa Basra 2.09 · Draw 2.66 · Gharraf 3.69
- Implied 1X2 · Al Minaa Basra 42.5% · Draw 33.4% · Gharraf 24.1%
- Bookmaker · Pinnacle
-
Aug 26, 2026 · 17:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Al Minaa Basra 2.09 · Draw 2.66 · Gharraf 3.69
- Implied 1X2 · Al Minaa Basra 42.5% · Draw 33.4% · Gharraf 24.1%
- Bookmaker · Pinnacle
-
Aug 26, 2026 · 18:00 UTC Kickoff
-
FT Full-time result Al Minaa Basra win · 3–0
-
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: Pass
- Statistical edge detected
- Direction agrees with model lean
- Validation passed
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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Iraqi League — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Al-Karma | 7 | 5 | 2 | 0 | 17 |
| 2 | Al Zawra'a | 7 | 4 | 3 | 0 | 15 |
| 3 | Erbil | 7 | 4 | 2 | 1 | 14 |
| 4 | Naft | 7 | 3 | 3 | 1 | 12 |
| 5 | Al Shorta | 7 | 3 | 3 | 1 | 12 |
| 6 | Newroz | 7 | 3 | 2 | 2 | 11 |
| 7 | Al-Jolan SC | 7 | 2 | 3 | 2 | 9 |
| 8 | Zakho | 7 | 2 | 3 | 2 | 9 |
| 9 | Al Talaba | 7 | 2 | 3 | 2 | 9 |
| 10 | Duhok | 7 | 1 | 5 | 1 | 8 |
| 11 | Diyala | 7 | 2 | 2 | 3 | 8 |
| 12 | Mosul | 7 | 2 | 2 | 3 | 8 |
| 13 | Al Minaa Basra | 7 | 2 | 2 | 3 | 8 |
| 14 | Al Quwa Al Jawiya | 7 | 1 | 4 | 2 | 7 |
| 15 | Ghaz Al Shamal | 7 | 1 | 4 | 2 | 7 |
| 16 | Al Kahrabaa | 7 | 1 | 4 | 2 | 7 |
| 17 | Naft Maysan | 7 | 1 | 4 | 2 | 7 |
| 18 | Karbala | 7 | 1 | 2 | 4 | 5 |
| 19 | Gharraf | 7 | 1 | 2 | 4 | 5 |
| 20 | Al Karkh | 7 | 1 | 1 | 5 | 4 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Al Zawra'a | 7 | 13 | 3 | +10 | 15 |
| 2 | Newroz | 7 | 13 | 4 | +9 | 11 |
| 3 | Al-Karma | 7 | 13 | 5 | +8 | 17 |
| 4 | Diyala | 7 | 12 | 13 | -1 | 8 |
| 5 | Duhok | 7 | 10 | 10 | 0 | 8 |
| 6 | Al Quwa Al Jawiya | 7 | 10 | 11 | -1 | 7 |
| 7 | Erbil | 7 | 9 | 3 | +6 | 14 |
| 8 | Mosul | 7 | 9 | 11 | -2 | 8 |
| 9 | Naft | 7 | 8 | 5 | +3 | 12 |
| 10 | Al Shorta | 7 | 7 | 4 | +3 | 12 |
| 11 | Al Minaa Basra | 7 | 7 | 9 | -2 | 8 |
| 12 | Zakho | 7 | 7 | 10 | -3 | 9 |
| 13 | Al Talaba | 7 | 7 | 12 | -5 | 9 |
| 14 | Al Karkh | 7 | 7 | 12 | -5 | 4 |
| 15 | Al-Jolan SC | 7 | 6 | 7 | -1 | 9 |
| 16 | Al Kahrabaa | 7 | 6 | 8 | -2 | 7 |
| 17 | Karbala | 7 | 6 | 12 | -6 | 5 |
| 18 | Ghaz Al Shamal | 7 | 4 | 5 | -1 | 7 |
| 19 | Naft Maysan | 7 | 4 | 8 | -4 | 7 |
| 20 | Gharraf | 7 | 4 | 10 | -6 | 5 |