The model missed the final outcome (Duhok win 2–1).
The model had projected Al Quwa Al Jawiya at 39.5%, 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 (3 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Al Quwa Al Jawiya Duhok ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 2-1 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Duhok | 31.0% | 33.5% | -2.5 pp | Aligned |
| Draw | 29.5% | 32.0% | -2.5 pp | Aligned |
| Al Quwa Al Jawiya | 39.5% | 34.5% | +5.0 pp | Aligned |
The statistical model estimates Al Quwa Al Jawiya's win probability at 39.5%, compared with the closing market's implied probability of 34.5%, a difference of 5.0 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 result was Duhok win 2–1.
Market Assessment
The fair estimate shows a modest edge over current market pricing on Al Quwa Al Jawiya.
- 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
- Both Teams To Score (Yes) matched the full-time result
- Exact score 2–1 fell within the model's highlighted bins
What failed
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
- 1X2: model leaned Al Quwa Al Jawiya; match finished Duhok
Market lesson
The closing market differed from the model on Al Quwa Al Jawiya by 5.0 percentage points (34.5% vs model 39.5%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 03, 2026 · 17:59 UTC Forecast generated
- Model 1X2 · Duhok 31.0% · Draw 29.5% · Al Quwa Al Jawiya 39.5%
- xG · Duhok 1.21 — Al Quwa Al Jawiya 1.39
-
Sep 03, 2026 · 17:30 UTC Opening odds snapshot PRE30
- 1X2 odds · Duhok 2.65 · Draw 2.78 · Al Quwa Al Jawiya 2.58
- Implied 1X2 · Duhok 33.5% · Draw 32.0% · Al Quwa Al Jawiya 34.5%
- Bookmaker · Pinnacle
-
Sep 03, 2026 · 17:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Duhok 2.65 · Draw 2.78 · Al Quwa Al Jawiya 2.58
- Implied 1X2 · Duhok 33.5% · Draw 32.0% · Al Quwa Al Jawiya 34.5%
- Bookmaker · Pinnacle
-
Sep 03, 2026 · 18:00 UTC Kickoff
-
FT Full-time result Duhok win · 2–1
-
FT Prediction missed 1X2 lean did not match 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
- No strong statistical edge
- 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 | 8 | 6 | 2 | 0 | 20 |
| 2 | Al Zawra'a | 8 | 5 | 3 | 0 | 18 |
| 3 | Erbil | 8 | 5 | 2 | 1 | 17 |
| 4 | Newroz | 8 | 4 | 3 | 1 | 15 |
| 5 | Al Shorta | 8 | 4 | 3 | 1 | 15 |
| 6 | Naft | 8 | 4 | 3 | 1 | 15 |
| 7 | Al-Jolan SC | 8 | 2 | 4 | 2 | 10 |
| 8 | Duhok | 8 | 1 | 6 | 1 | 9 |
| 9 | Diyala | 8 | 2 | 3 | 3 | 9 |
| 10 | Al Minaa Basra | 8 | 2 | 3 | 3 | 9 |
| 11 | Zakho | 8 | 2 | 3 | 3 | 9 |
| 12 | Al Quwa Al Jawiya | 8 | 1 | 5 | 2 | 8 |
| 13 | Ghaz Al Shamal | 8 | 1 | 5 | 2 | 8 |
| 14 | Mosul | 8 | 2 | 2 | 4 | 8 |
| 15 | Al Karkh | 8 | 2 | 1 | 5 | 7 |
| 16 | Al Kahrabaa | 8 | 1 | 4 | 3 | 7 |
| 17 | Al Talaba | 8 | 1 | 4 | 3 | 7 |
| 18 | Naft Maysan | 8 | 1 | 4 | 3 | 7 |
| 19 | Gharraf | 8 | 1 | 2 | 5 | 5 |
| 20 | Karbala | 8 | 1 | 2 | 5 | 5 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Al Zawra'a | 8 | 15 | 3 | +12 | 18 |
| 2 | Al-Karma | 8 | 14 | 5 | +9 | 20 |
| 3 | Newroz | 8 | 13 | 4 | +9 | 15 |
| 4 | Diyala | 8 | 13 | 14 | -1 | 9 |
| 5 | Erbil | 8 | 12 | 3 | +9 | 17 |
| 6 | Duhok | 8 | 11 | 11 | 0 | 9 |
| 7 | Al Quwa Al Jawiya | 8 | 11 | 12 | -1 | 8 |
| 8 | Al Karkh | 8 | 10 | 14 | -4 | 7 |
| 9 | Al Shorta | 8 | 9 | 4 | +5 | 15 |
| 10 | Naft | 8 | 9 | 5 | +4 | 15 |
| 11 | Mosul | 8 | 9 | 12 | -3 | 8 |
| 12 | Al Talaba | 8 | 9 | 14 | -5 | 7 |
| 13 | Al-Jolan SC | 8 | 8 | 9 | -1 | 10 |
| 14 | Al Minaa Basra | 8 | 8 | 10 | -2 | 9 |
| 15 | Zakho | 8 | 7 | 11 | -4 | 9 |
| 16 | Al Kahrabaa | 8 | 6 | 10 | -4 | 7 |
| 17 | Naft Maysan | 8 | 6 | 11 | -5 | 7 |
| 18 | Karbala | 8 | 6 | 15 | -9 | 5 |
| 19 | Ghaz Al Shamal | 8 | 4 | 5 | -1 | 8 |
| 20 | Gharraf | 8 | 4 | 12 | -8 | 5 |