AI correctly predicted the Larisa win.
The match finished 1–0, 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 (1 goals) ✔ Correct
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Larisa Larisa ✔ Correct
- Correct Score Insights 1-1, 1-0, 2-1, 2-0, 0-1 1-0 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Larisa | 45.3% | 60.7% | -15.3 pp | Market Higher |
| Draw | 28.9% | 23.2% | +5.7 pp | Model Higher |
| PAOK II | 25.8% | 16.1% | +9.7 pp | Model Higher |
The closing market estimates Larisa's win probability at 60.7%, compared with the model's estimate of 45.3%, a difference of 15.3 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: PRE10.
After full time, the model's directional lean matched the result (Larisa win 1–0).
Market Assessment
The market is materially more optimistic about Larisa 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
- Larisa attacking xG significantly stronger (1.51 vs 1.09)
- Under 2.5 goals aligned with the xG profile
- Exact score 1–0 fell within the model's highlighted bins
What failed
- Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Larisa higher (60.6% vs model 45.3%, 15.3 pp), but the model's lean was validated (Larisa win 1–0).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 27, 2026 · 13:02 UTC Forecast generated
- Model 1X2 · Larisa 45.3% · Draw 28.9% · PAOK II 25.8%
- xG · Larisa 1.51 — PAOK II 1.09
-
Sep 27, 2026 · 12:44 UTC Opening odds snapshot PRE30
- 1X2 odds · Larisa 1.53 · Draw 4.00 · PAOK II 5.75
- Implied 1X2 · Larisa 60.7% · Draw 23.2% · PAOK II 16.1%
- Bookmaker · Bet365
-
Sep 27, 2026 · 13:02 UTC Closing snapshot recorded PRE10
- 1X2 odds · Larisa 1.53 · Draw 4.00 · PAOK II 5.75
- Implied 1X2 · Larisa 60.7% · Draw 23.2% · PAOK II 16.1%
- Bookmaker · Bet365
-
Sep 27, 2026 · 13:00 UTC Kickoff
-
FT Full-time result Larisa win · 1–0
-
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 (15 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 2 — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Larisa | 4 | 3 | 1 | 0 | 10 |
| 2 | Panionios | 4 | 3 | 1 | 0 | 10 |
| 3 | Marko | 3 | 3 | 0 | 0 | 9 |
| 4 | Ellas Syros | 4 | 2 | 2 | 0 | 8 |
| 5 | Panthrakikos | 3 | 2 | 1 | 0 | 7 |
| 6 | Panserraikos | 4 | 2 | 0 | 2 | 6 |
| 7 | Kallithea | 3 | 2 | 0 | 1 | 6 |
| 8 | Apollon Pontou | 4 | 1 | 1 | 2 | 4 |
| 9 | Nestos Chrisoupolis | 4 | 1 | 1 | 2 | 4 |
| 10 | PAOK II | 4 | 1 | 1 | 2 | 4 |
| 11 | Olympiakos Piraeus II | 4 | 1 | 1 | 2 | 4 |
| 12 | Niki Volos | 4 | 1 | 0 | 3 | 3 |
| 13 | Asteras Tripolis II | 3 | 1 | 0 | 2 | 3 |
| 14 | Anagennisi Karditsas | 4 | 0 | 2 | 2 | 2 |
| 15 | Pyrgos 1968 | 4 | 0 | 2 | 2 | 2 |
| 16 | Zakynthos | 4 | 0 | 1 | 3 | 1 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Ellas Syros | 4 | 9 | 3 | +6 | 8 |
| 2 | Larisa | 4 | 7 | 1 | +6 | 10 |
| 3 | Marko | 3 | 7 | 3 | +4 | 9 |
| 4 | Panserraikos | 4 | 6 | 4 | +2 | 6 |
| 5 | Olympiakos Piraeus II | 4 | 6 | 10 | -4 | 4 |
| 6 | Kallithea | 3 | 5 | 4 | +1 | 6 |
| 7 | Panionios | 4 | 4 | 0 | +4 | 10 |
| 8 | Niki Volos | 4 | 4 | 5 | -1 | 3 |
| 9 | Panthrakikos | 3 | 3 | 0 | +3 | 7 |
| 10 | Apollon Pontou | 4 | 3 | 4 | -1 | 4 |
| 11 | Nestos Chrisoupolis | 4 | 3 | 5 | -2 | 4 |
| 12 | PAOK II | 4 | 3 | 5 | -2 | 4 |
| 13 | Zakynthos | 4 | 2 | 7 | -5 | 1 |
| 14 | Asteras Tripolis II | 3 | 1 | 3 | -2 | 3 |
| 15 | Anagennisi Karditsas | 4 | 1 | 5 | -4 | 2 |
| 16 | Pyrgos 1968 | 4 | 0 | 5 | -5 | 2 |
