AI correctly predicted the Sabah FA win.
The match finished 2–0, 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 Under 2.5 (2 goals) ✔ Correct
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Sabah FA Sabah FA ✔ Correct
- Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 2-0 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Sabah FA | 36.6% | 54.4% | -17.8 pp | Market Higher |
| Draw | 29.6% | 24.7% | +4.9 pp | Aligned |
| Penang | 33.8% | 20.9% | +12.9 pp | Model Edge |
The closing market estimates Sabah FA's win probability at 54.4%, compared with the model's estimate of 36.6%, a difference of 17.8 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 (Sabah FA win 2–0).
Market Assessment
The market is materially more optimistic about Sabah FA 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
- Under 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
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Sabah FA higher (54.4% vs model 36.6%, 17.8 pp), but the model's lean was validated (Sabah FA win 2–0).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 28, 2026 · 11:29 UTC Forecast generated
- Model 1X2 · Sabah FA 36.6% · Draw 29.6% · Penang 33.8%
- xG · Sabah FA 1.33 — Penang 1.27
-
Aug 28, 2026 · 10:59 UTC Opening odds snapshot PRE30
- 1X2 odds · Sabah FA 1.68 · Draw 3.70 · Penang 4.37
- Implied 1X2 · Sabah FA 54.4% · Draw 24.7% · Penang 20.9%
- Bookmaker · Pinnacle
-
Aug 28, 2026 · 11:29 UTC Closing snapshot recorded PRE1
- 1X2 odds · Sabah FA 1.68 · Draw 3.70 · Penang 4.37
- Implied 1X2 · Sabah FA 54.4% · Draw 24.7% · Penang 20.9%
- Bookmaker · Pinnacle
-
Aug 28, 2026 · 11:30 UTC Kickoff
-
FT Full-time result Sabah FA win · 2–0
-
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 (18 pp)
- No strong statistical edge
- Pricing remains divergent
- 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 |
