The model missed the final outcome (Inter U23 win 1–2).
The model had projected Catania at 39.5%, 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 Under 2.5 Over 2.5 (3 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Catania Inter U23 ✖ Incorrect
- Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-2 ✔ Correct
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Catania | 39.5% | 59.4% | -19.9 pp | Market Higher |
| Draw | 29.5% | 25.3% | +4.2 pp | Aligned |
| Inter U23 | 31.0% | 15.3% | +15.7 pp | Model Edge |
The closing market estimates Catania's win probability at 59.4%, compared with the model's estimate of 39.5%, a difference of 19.9 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: PRE5.
After full time, the result was Inter U23 win 1–2.
Market Assessment
The market is materially more optimistic about Catania 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
- Both Teams To Score (Yes) matched the full-time result
- Exact score 1–2 fell within the model's highlighted bins
What failed
- Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (3 goals)
- 1X2: model leaned Catania; match finished Inter U23
Market lesson
The closing market differed from the model on Catania by 19.9 percentage points (59.4% vs model 39.5%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 23, 2026 · 16:01 UTC Forecast generated
- Model 1X2 · Catania 39.5% · Draw 29.5% · Inter U23 31.0%
- xG · Catania 1.39 — Inter U23 1.21
-
Aug 23, 2026 · 15:36 UTC Opening odds snapshot PRE30
- 1X2 odds · Catania 1.56 · Draw 3.66 · Inter U23 6.05
- Implied 1X2 · Catania 59.4% · Draw 25.3% · Inter U23 15.3%
- Bookmaker · Pinnacle
-
Aug 23, 2026 · 16:01 UTC Closing snapshot recorded PRE5
- 1X2 odds · Catania 1.56 · Draw 3.66 · Inter U23 6.05
- Implied 1X2 · Catania 59.4% · Draw 25.3% · Inter U23 15.3%
- Bookmaker · Pinnacle
-
Aug 23, 2026 · 16:00 UTC Kickoff
-
FT Full-time result Inter U23 win · 1–2
-
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 (20 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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Serie C - Girone C — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Sorrento | 4 | 4 | 0 | 0 | 12 |
| 2 | Audace Cerignola | 4 | 3 | 0 | 1 | 9 |
| 3 | AZ Picerno | 4 | 3 | 0 | 1 | 9 |
| 4 | Bari | 4 | 3 | 0 | 1 | 9 |
| 5 | Potenza | 4 | 3 | 0 | 1 | 9 |
| 6 | Casertana | 4 | 2 | 2 | 0 | 8 |
| 7 | SS Monopoli | 4 | 2 | 0 | 2 | 6 |
| 8 | Casarano | 4 | 2 | 0 | 2 | 6 |
| 9 | Barletta | 4 | 1 | 2 | 1 | 5 |
| 10 | Salernitana | 4 | 1 | 2 | 1 | 5 |
| 11 | Scafatese | 4 | 1 | 2 | 1 | 5 |
| 12 | Cavese | 4 | 1 | 2 | 1 | 5 |
| 13 | Savoia | 4 | 1 | 1 | 2 | 4 |
| 14 | Foggia | 4 | 1 | 1 | 2 | 4 |
| 15 | Inter U23 | 4 | 1 | 1 | 2 | 4 |
| 16 | Team Altamura | 4 | 1 | 1 | 2 | 4 |
| 17 | Catania | 4 | 1 | 0 | 3 | 3 |
| 18 | Giugliano | 4 | 0 | 1 | 3 | 1 |
| 19 | Cosenza | 4 | 0 | 1 | 3 | 1 |
| 20 | Crotone | 4 | 0 | 2 | 2 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Audace Cerignola | 4 | 10 | 4 | +6 | 9 |
| 2 | Casertana | 4 | 10 | 8 | +2 | 8 |
| 3 | AZ Picerno | 4 | 9 | 4 | +5 | 9 |
| 4 | Potenza | 4 | 9 | 6 | +3 | 9 |
| 5 | Barletta | 4 | 9 | 8 | +1 | 5 |
| 6 | Casarano | 4 | 8 | 9 | -1 | 6 |
| 7 | Bari | 4 | 7 | 3 | +4 | 9 |
| 8 | Salernitana | 4 | 7 | 6 | +1 | 5 |
| 9 | Scafatese | 4 | 7 | 8 | -1 | 5 |
| 10 | Sorrento | 4 | 6 | 1 | +5 | 12 |
| 11 | Savoia | 4 | 6 | 6 | 0 | 4 |
| 12 | Catania | 4 | 6 | 6 | 0 | 3 |
| 13 | Inter U23 | 4 | 6 | 9 | -3 | 4 |
| 14 | Giugliano | 4 | 6 | 13 | -7 | 1 |
| 15 | Cavese | 4 | 4 | 5 | -1 | 5 |
| 16 | SS Monopoli | 4 | 3 | 2 | +1 | 6 |
| 17 | Crotone | 4 | 3 | 5 | -2 | |
| 18 | Foggia | 4 | 2 | 4 | -2 | 4 |
| 19 | Team Altamura | 4 | 2 | 6 | -4 | 4 |
| 20 | Cosenza | 4 | 2 | 9 | -7 | 1 |