The model missed the final outcome (Apollon Pontou win 1–0).
The model had projected Anagennisi Karditsas at 38.5%, 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 Over 2.5 Under 2.5 (1 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Anagennisi Karditsas Apollon Pontou ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-0 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Apollon Pontou | 31.9% | 26.6% | +5.3 pp | Model Higher |
| Draw | 29.6% | 31.1% | -1.5 pp | Aligned |
| Anagennisi Karditsas | 38.5% | 42.3% | -3.9 pp | Aligned |
The statistical model estimates Apollon Pontou's win probability at 31.9%, compared with the closing market's implied probability of 26.6%, a difference of 5.3 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 result was Apollon Pontou win 1–0.
Market Assessment
The fair estimate shows a modest edge over current market pricing on Apollon Pontou.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- 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
- Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (1 goals)
Market lesson
The closing market differed from the model on Anagennisi Karditsas by 5.3 percentage points (33.2% vs model 38.5%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 27, 2026 · 13:02 UTC Forecast generated
- Model 1X2 · Apollon Pontou 31.9% · Draw 29.6% · Anagennisi Karditsas 38.5%
- xG · Apollon Pontou 1.23 — Anagennisi Karditsas 1.37
-
Sep 27, 2026 · 12:44 UTC Opening odds snapshot PRE30
- 1X2 odds · Apollon Pontou 3.50 · Draw 3.00 · Anagennisi Karditsas 2.20
- Implied 1X2 · Apollon Pontou 26.6% · Draw 31.1% · Anagennisi Karditsas 42.3%
- Bookmaker · Bet365
-
Sep 27, 2026 · 13:02 UTC Closing snapshot recorded PRE10
- 1X2 odds · Apollon Pontou 3.50 · Draw 3.00 · Anagennisi Karditsas 2.20
- Implied 1X2 · Apollon Pontou 26.6% · Draw 31.1% · Anagennisi Karditsas 42.3%
- Bookmaker · Bet365
-
Sep 27, 2026 · 13:00 UTC Kickoff
-
FT Full-time result Apollon Pontou win · 1–0
-
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 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 |
