The model missed the final outcome (Jarosław win 6–2).
The model had projected Korona Kielce II at 37.1%, 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 (8 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Korona Kielce II Jarosław ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 6-2 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Jarosław | 33.3% | 52.2% | -18.9 pp | Market Higher |
| Draw | 29.6% | 23.2% | +6.5 pp | Model Higher |
| Korona Kielce II | 37.1% | 24.6% | +12.4 pp | Model Edge |
The closing market estimates Jarosław's win probability at 52.2%, compared with the model's estimate of 33.3%, a difference of 18.9 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 Jarosław win 6–2.
Market Assessment
The market is materially more optimistic about Jarosław 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) — 8 goals materialised
- Both Teams To Score (Yes) matched the full-time result
What failed
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (8 goals)
- 1X2: model leaned Korona Kielce II; match finished Jarosław
Market lesson
The closing market differed from the model on Korona Kielce II by 18.9 percentage points (56.0% vs model 37.1%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 05, 2026 · 14:13 UTC Forecast generated
- Model 1X2 · Jarosław 33.4% · Draw 29.6% · Korona Kielce II 37.0%
- xG · Jarosław 1.26 — Korona Kielce II 1.34
-
Sep 05, 2026 · 13:47 UTC Opening odds snapshot PRE30
- 1X2 odds · Jarosław 1.70 · Draw 3.83 · Korona Kielce II 3.60
- Implied 1X2 · Jarosław 52.2% · Draw 23.2% · Korona Kielce II 24.6%
- Bookmaker · Pinnacle
-
Sep 05, 2026 · 14:13 UTC Closing snapshot recorded PRE1
- 1X2 odds · Jarosław 1.70 · Draw 3.83 · Korona Kielce II 3.60
- Implied 1X2 · Jarosław 52.2% · Draw 23.2% · Korona Kielce II 24.6%
- Bookmaker · Pinnacle
-
Sep 05, 2026 · 14:00 UTC Kickoff
-
FT Full-time result Jarosław win · 6–2
-
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: 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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III Liga - Group 4 — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Chełmianka Chełm | 10 | 8 | 2 | 0 | 26 |
| 2 | KSZO 1929 | 9 | 5 | 4 | 0 | 19 |
| 3 | Czarni Połaniec | 10 | 6 | 1 | 3 | 19 |
| 4 | Wisłoka Dębica | 10 | 6 | 1 | 3 | 19 |
| 5 | Wiślanie Jaśkowice | 10 | 5 | 2 | 3 | 17 |
| 6 | Naprzód | 10 | 5 | 2 | 3 | 17 |
| 7 | Jarosław | 9 | 5 | 1 | 3 | 16 |
| 8 | Siarka Tarnobrzeg | 10 | 4 | 2 | 4 | 14 |
| 9 | Wisła Kraków II | 10 | 3 | 4 | 3 | 13 |
| 10 | Sokół Kolb. | 10 | 2 | 6 | 2 | 12 |
| 11 | Podlasie Biała Podlaska | 10 | 3 | 2 | 5 | 11 |
| 12 | Busko-Zdroj | 10 | 3 | 2 | 5 | 11 |
| 13 | Hetman Zamosc | 9 | 2 | 4 | 3 | 10 |
| 14 | Star Starachowice | 10 | 2 | 4 | 4 | 10 |
| 15 | Korona Kielce II | 10 | 2 | 2 | 6 | 8 |
| 16 | KS Wieczysta Krakow II | 10 | 2 | 2 | 6 | 8 |
| 17 | Pogoń-Sokół Lubaczów | 10 | 2 | 1 | 7 | 7 |
| 18 | Moravia Morawica | 9 | 2 | 0 | 7 | 6 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Jarosław | 9 | 24 | 15 | +9 | 16 |
| 2 | Naprzód | 10 | 24 | 20 | +4 | 17 |
| 3 | Korona Kielce II | 10 | 21 | 26 | -5 | 8 |
| 4 | Czarni Połaniec | 10 | 17 | 15 | +2 | 19 |
| 5 | Chełmianka Chełm | 10 | 16 | 3 | +13 | 26 |
| 6 | Hetman Zamosc | 9 | 16 | 17 | -1 | 10 |
| 7 | Wiślanie Jaśkowice | 10 | 15 | 10 | +5 | 17 |
| 8 | KSZO 1929 | 9 | 14 | 6 | +8 | 19 |
| 9 | Wisłoka Dębica | 10 | 14 | 12 | +2 | 19 |
| 10 | Busko-Zdroj | 10 | 14 | 21 | -7 | 11 |
| 11 | Siarka Tarnobrzeg | 10 | 13 | 13 | 0 | 14 |
| 12 | Wisła Kraków II | 10 | 13 | 13 | 0 | 13 |
| 13 | Star Starachowice | 10 | 11 | 15 | -4 | 10 |
| 14 | Sokół Kolb. | 10 | 10 | 10 | 0 | 12 |
| 15 | Pogoń-Sokół Lubaczów | 10 | 10 | 19 | -9 | 7 |
| 16 | KS Wieczysta Krakow II | 10 | 9 | 14 | -5 | 8 |
| 17 | Moravia Morawica | 9 | 9 | 18 | -9 | 6 |
| 18 | Podlasie Biała Podlaska | 10 | 8 | 11 | -3 | 11 |