The model missed the final outcome (Ujpest win 2–1).
The model had projected Zalaegerszegi TE at 36.1%, 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 No Yes ✖ Incorrect
- 1X2 Zalaegerszegi TE Ujpest ✖ 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 |
|---|---|---|---|---|
| Ujpest | 34.2% | 52.8% | -18.6 pp | Market Higher |
| Draw | 29.6% | 24.4% | +5.2 pp | Model Higher |
| Zalaegerszegi TE | 36.1% | 22.8% | +13.3 pp | Model Edge |
The closing market estimates Ujpest's win probability at 52.8%, compared with the model's estimate of 34.2%, a difference of 18.6 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 result was Ujpest win 2–1.
Market Assessment
The market is materially more optimistic about Ujpest 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
- Expected goals projected a high-scoring match (ΣxG 2.60) — 3 goals materialised
- Exact score 2–1 fell within the model's highlighted bins
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 (3 goals)
Market lesson
The closing market differed from the model on Zalaegerszegi TE by 18.6 percentage points (54.7% vs model 36.1%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 20, 2026 · 14:50 UTC Forecast generated
- Model 1X2 · Ujpest 34.2% · Draw 29.7% · Zalaegerszegi TE 36.1%
- xG · Ujpest 1.28 — Zalaegerszegi TE 1.32
-
Sep 20, 2026 · 12:14 UTC Opening odds snapshot PRE30
- 1X2 odds · Ujpest 1.80 · Draw 3.89 · Zalaegerszegi TE 4.17
- Implied 1X2 · Ujpest 52.8% · Draw 24.4% · Zalaegerszegi TE 22.8%
- Bookmaker · Pinnacle
-
Sep 20, 2026 · 12:44 UTC Closing snapshot recorded PRE1
- 1X2 odds · Ujpest 1.80 · Draw 3.89 · Zalaegerszegi TE 4.17
- Implied 1X2 · Ujpest 52.8% · Draw 24.4% · Zalaegerszegi TE 22.8%
- Bookmaker · Pinnacle
-
Sep 20, 2026 · 15:00 UTC Kickoff
-
FT Full-time result Ujpest 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: Warning
- Large market gap (19 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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NB I — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Gyori ETO FC | 8 | 4 | 3 | 1 | 15 |
| 2 | Puskas Academy | 8 | 5 | 0 | 3 | 15 |
| 3 | Vasas | 8 | 4 | 2 | 2 | 14 |
| 4 | Ujpest | 8 | 4 | 2 | 2 | 14 |
| 5 | Ferencvarosi TC | 7 | 3 | 3 | 1 | 12 |
| 6 | Paks | 8 | 3 | 2 | 3 | 11 |
| 7 | MTK Budapest | 8 | 2 | 3 | 3 | 9 |
| 8 | Kisvarda FC | 8 | 2 | 3 | 3 | 9 |
| 9 | Debreceni VSC | 8 | 2 | 3 | 3 | 9 |
| 10 | Nyiregyhaza | 8 | 2 | 2 | 4 | 8 |
| 11 | Budapest Honved | 7 | 1 | 3 | 3 | 6 |
| 12 | Zalaegerszegi TE | 8 | 2 | 0 | 6 | 6 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Vasas | 8 | 17 | 11 | +6 | 14 |
| 2 | Ujpest | 8 | 17 | 13 | +4 | 14 |
| 3 | Gyori ETO FC | 8 | 16 | 10 | +6 | 15 |
| 4 | Paks | 8 | 16 | 17 | -1 | 11 |
| 5 | MTK Budapest | 8 | 15 | 14 | +1 | 9 |
| 6 | Puskas Academy | 8 | 13 | 10 | +3 | 15 |
| 7 | Debreceni VSC | 8 | 12 | 15 | -3 | 9 |
| 8 | Ferencvarosi TC | 7 | 11 | 8 | +3 | 12 |
| 9 | Budapest Honved | 7 | 11 | 14 | -3 | 6 |
| 10 | Kisvarda FC | 8 | 9 | 10 | -1 | 9 |
| 11 | Nyiregyhaza | 8 | 9 | 14 | -5 | 8 |
| 12 | Zalaegerszegi TE | 8 | 7 | 17 | -10 | 6 |
