AI correctly predicted the Selangor 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 No No ✔ Correct
- 1X2 Selangor Selangor ✔ Correct
- Correct Score Insights 1-1, 1-0, 2-1, 2-0, 0-1 3-0 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Selangor | 44.8% | 73.1% | -28.3 pp | Market Higher |
| Draw | 28.9% | 15.7% | +13.2 pp | Model Edge |
| Kuala Lumpur FA | 26.2% | 11.2% | +15.1 pp | Model Edge |
The closing market estimates Selangor's win probability at 73.1%, compared with the model's estimate of 44.8%, a difference of 28.3 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 (Selangor win 3–0).
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
- Selangor attacking xG significantly stronger (1.50 vs 1.10)
- Both Teams To Score (No) matched the full-time result
What failed
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
- Exact score: outside the model's top score bins
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Selangor higher (73.1% vs model 44.8%, 28.3 pp), but the model's lean was validated (Selangor win 3–0).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 13, 2026 · 12:14 UTC Forecast generated
- Model 1X2 · Selangor 44.8% · Draw 29.0% · Kuala Lumpur FA 26.2%
- xG · Selangor 1.50 — Kuala Lumpur FA 1.10
-
Sep 13, 2026 · 11:44 UTC Opening odds snapshot PRE30
- 1X2 odds · Selangor 1.23 · Draw 5.73 · Kuala Lumpur FA 8.05
- Implied 1X2 · Selangor 73.1% · Draw 15.7% · Kuala Lumpur FA 11.2%
- Bookmaker · Pinnacle
-
Sep 13, 2026 · 12:14 UTC Closing snapshot recorded PRE1
- 1X2 odds · Selangor 1.23 · Draw 5.73 · Kuala Lumpur FA 8.05
- Implied 1X2 · Selangor 73.1% · Draw 15.7% · Kuala Lumpur FA 11.2%
- Bookmaker · Pinnacle
-
Sep 13, 2026 · 12:15 UTC Kickoff
-
FT Full-time result Selangor 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.
Historical label: Originally displayed as "Wait for validation".
Pre-match metrics (historical context)
- Validation: Warning
- Large market gap (28 pp)
- No strong statistical edge
- Market strongly disagrees on price
- 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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Super League — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Johor Darul Takzim FC | 5 | 5 | 0 | 0 | 15 |
| 2 | Kuching FA | 5 | 4 | 0 | 1 | 12 |
| 3 | Selangor | 4 | 4 | 0 | 0 | 12 |
| 4 | Sabah FA | 4 | 2 | 0 | 2 | 6 |
| 5 | DPMM FC | 4 | 2 | 0 | 2 | 6 |
| 6 | Kuala Lumpur FA | 5 | 2 | 0 | 3 | 6 |
| 7 | Terengganu | 4 | 1 | 2 | 1 | 5 |
| 8 | Negeri Sembilan | 4 | 1 | 1 | 2 | 4 |
| 9 | Penang | 4 | 1 | 1 | 2 | 4 |
| 10 | Melaka | 4 | 1 | 0 | 3 | 3 |
| 11 | Imigresen | 4 | 0 | 2 | 2 | 2 |
| 12 | Kelantan Red Warrior FC | 5 | 0 | 0 | 5 | 0 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Johor Darul Takzim FC | 5 | 25 | 0 | +25 | 15 |
| 2 | Kuching FA | 5 | 15 | 4 | +11 | 12 |
| 3 | Selangor | 4 | 13 | 3 | +10 | 12 |
| 4 | Sabah FA | 4 | 6 | 5 | +1 | 6 |
| 5 | Negeri Sembilan | 4 | 6 | 7 | -1 | 4 |
| 6 | Melaka | 4 | 5 | 9 | -4 | 3 |
| 7 | Terengganu | 4 | 4 | 4 | 0 | 5 |
| 8 | Kuala Lumpur FA | 5 | 4 | 13 | -9 | 6 |
| 9 | Imigresen | 4 | 4 | 13 | -9 | 2 |
| 10 | Kelantan Red Warrior FC | 5 | 4 | 24 | -20 | 0 |
| 11 | DPMM FC | 4 | 3 | 5 | -2 | 6 |
| 12 | Penang | 4 | 3 | 5 | -2 | 4 |
