The model missed the final outcome (Dukla Banská Bystrica win 3–2).
The model had projected Skalica at 35.6%, 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 (5 goals) ✖ Incorrect
- Both Teams To Score BTTS No Yes ✖ Incorrect
- 1X2 Skalica Dukla Banská Bystrica ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 3-2 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Dukla Banská Bystrica | 34.7% | 41.1% | -6.4 pp | Market Higher |
| Draw | 29.6% | 27.7% | +1.9 pp | Aligned |
| Skalica | 35.6% | 31.2% | +4.4 pp | Aligned |
The closing market estimates Dukla Banská Bystrica's win probability at 41.1%, compared with the model's estimate of 34.7%, a difference of 6.4 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: PRE5.
After full time, the result was Dukla Banská Bystrica win 3–2.
Market Assessment
The market and model broadly agree on Dukla Banská Bystrica. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 2.60) — 5 goals materialised
What failed
- Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (5 goals)
Market lesson
The closing market differed from the model on Skalica by 6.4 percentage points (42.0% vs model 35.6%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 12, 2026 · 15:55 UTC Forecast generated
- Model 1X2 · Dukla Banská Bystrica 34.7% · Draw 29.7% · Skalica 35.6%
- xG · Dukla Banská Bystrica 1.29 — Skalica 1.31
-
Sep 12, 2026 · 15:31 UTC Opening odds snapshot PRE30
- 1X2 odds · Dukla Banská Bystrica 2.32 · Draw 3.44 · Skalica 3.05
- Implied 1X2 · Dukla Banská Bystrica 41.1% · Draw 27.7% · Skalica 31.2%
- Bookmaker · Pinnacle
-
Sep 12, 2026 · 15:55 UTC Closing snapshot recorded PRE5
- 1X2 odds · Dukla Banská Bystrica 2.32 · Draw 3.44 · Skalica 3.05
- Implied 1X2 · Dukla Banská Bystrica 41.1% · Draw 27.7% · Skalica 31.2%
- Bookmaker · Pinnacle
-
Sep 12, 2026 · 16:00 UTC Kickoff
-
FT Full-time result Dukla Banská Bystrica win · 3–2
-
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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Super Liga — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Dunajska Streda | 8 | 6 | 2 | 0 | 20 |
| 2 | Žilina | 9 | 6 | 2 | 1 | 20 |
| 3 | Spartak Trnava | 9 | 5 | 3 | 1 | 18 |
| 4 | Slovan Bratislava | 8 | 5 | 1 | 2 | 16 |
| 5 | Podbrezová | 9 | 4 | 2 | 3 | 14 |
| 6 | Zemplín Michalovce | 9 | 4 | 1 | 4 | 13 |
| 7 | FK Košice | 8 | 3 | 3 | 2 | 12 |
| 8 | Skalica | 9 | 2 | 2 | 5 | 8 |
| 9 | Dukla Banská Bystrica | 9 | 2 | 1 | 6 | 7 |
| 10 | Komárno | 9 | 0 | 5 | 4 | 5 |
| 11 | AS Trencin | 8 | 1 | 2 | 5 | 5 |
| 12 | Ružomberok | 9 | 1 | 2 | 6 | 5 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Dunajska Streda | 8 | 25 | 5 | +20 | 20 |
| 2 | Žilina | 9 | 23 | 17 | +6 | 20 |
| 3 | Spartak Trnava | 9 | 21 | 10 | +11 | 18 |
| 4 | FK Košice | 8 | 21 | 18 | +3 | 12 |
| 5 | Slovan Bratislava | 8 | 20 | 9 | +11 | 16 |
| 6 | Podbrezová | 9 | 13 | 16 | -3 | 14 |
| 7 | Skalica | 9 | 11 | 19 | -8 | 8 |
| 8 | AS Trencin | 8 | 10 | 20 | -10 | 5 |
| 9 | Zemplín Michalovce | 9 | 9 | 11 | -2 | 13 |
| 10 | Dukla Banská Bystrica | 9 | 9 | 21 | -12 | 7 |
| 11 | Komárno | 9 | 8 | 14 | -6 | 5 |
| 12 | Ružomberok | 9 | 8 | 18 | -10 | 5 |
