The model missed the final outcome (Inter Milano W win 3–1).
The model had projected VfL Wolfsburg W at 38.0%, 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 (4 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 VfL Wolfsburg W Inter Milano W ✖ Incorrect
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 3-1 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Inter Milano W | 32.4% | 30.3% | +2.0 pp | Aligned |
| Draw | 29.6% | 25.4% | +4.2 pp | Aligned |
| VfL Wolfsburg W | 38.0% | 44.3% | -6.3 pp | Market Higher |
The closing market estimates VfL Wolfsburg W's win probability at 44.3%, compared with the model's estimate of 38.0%, a difference of 6.3 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: PRE1.
After full time, the result was Inter Milano W win 3–1.
Market Assessment
The market and model broadly agree on VfL Wolfsburg W. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.
- Monitor line movement before kickoff — not a betting recommendation.
Post Match Insights
What worked
- Expected goals projected a high-scoring match (ΣxG 2.60) — 4 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 (4 goals)
- 1X2: model leaned VfL Wolfsburg W; match finished Inter Milano W
Market lesson
The closing market differed from the model on VfL Wolfsburg W by 6.3 percentage points (44.3% vs model 38.0%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 02, 2026 · 16:29 UTC Forecast generated
- Model 1X2 · Inter Milano W 32.4% · Draw 29.6% · VfL Wolfsburg W 38.0%
- xG · Inter Milano W 1.24 — VfL Wolfsburg W 1.36
-
Sep 02, 2026 · 16:01 UTC Opening odds snapshot PRE30
- 1X2 odds · Inter Milano W 3.02 · Draw 3.61 · VfL Wolfsburg W 2.07
- Implied 1X2 · Inter Milano W 30.3% · Draw 25.4% · VfL Wolfsburg W 44.3%
- Bookmaker · Pinnacle
-
Sep 02, 2026 · 16:29 UTC Closing snapshot recorded PRE1
- 1X2 odds · Inter Milano W 3.02 · Draw 3.61 · VfL Wolfsburg W 2.07
- Implied 1X2 · Inter Milano W 30.3% · Draw 25.4% · VfL Wolfsburg W 44.3%
- Bookmaker · Pinnacle
-
Sep 02, 2026 · 16:30 UTC Kickoff
-
FT Full-time result Inter Milano W win · 3–1
-
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: 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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UEFA Champions League Women — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Lyon W | 1 | 1 | 0 | 0 | 3 |
| 2 | Barcelona W | 1 | 1 | 0 | 0 | 3 |
| 3 | SL Benfica | 1 | 1 | 0 | 0 | 3 |
| 4 | Arsenal W | 1 | 1 | 0 | 0 | 3 |
| 5 | Chelsea W | 1 | 1 | 0 | 0 | 3 |
| 6 | Inter Milano W | 1 | 1 | 0 | 0 | 3 |
| 7 | Manchester City W | 1 | 0 | 1 | 0 | 1 |
| 8 | Bayern Munich W | 1 | 0 | 1 | 0 | 1 |
| 9 | Paris Saint Germain W | 1 | 0 | 1 | 0 | 1 |
| 10 | Real Madrid W | 1 | 0 | 1 | 0 | 1 |
| 11 | OH Leuven W | 1 | 0 | 1 | 0 | 1 |
| 12 | Roma W | 1 | 0 | 1 | 0 | 1 |
| 13 | Juventus W | 1 | 0 | 0 | 1 | 0 |
| 14 | Austria Wien W | 1 | 0 | 0 | 1 | 0 |
| 15 | Häcken | 1 | 0 | 0 | 1 | 0 |
| 16 | Køge | 1 | 0 | 0 | 1 | 0 |
| 17 | Paris FC W | 1 | 0 | 0 | 1 | 0 |
| 18 | Servette Chênois W | 1 | 0 | 0 | 1 | 0 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Lyon W | 1 | 8 | 0 | +8 | 3 |
| 2 | Barcelona W | 1 | 5 | 2 | +3 | 3 |
| 3 | SL Benfica | 1 | 2 | 1 | +1 | 3 |
| 4 | Manchester City W | 1 | 2 | 2 | 0 | 1 |
| 5 | Bayern Munich W | 1 | 2 | 2 | 0 | 1 |
| 6 | Paris FC W | 1 | 2 | 5 | -3 | 0 |
| 7 | Arsenal W | 1 | 1 | 0 | +1 | 3 |
| 8 | Chelsea W | 1 | 1 | 0 | +1 | 3 |
| 9 | Inter Milano W | 1 | 1 | 0 | +1 | 3 |
| 10 | Paris Saint Germain W | 1 | 1 | 1 | 0 | 1 |
| 11 | Real Madrid W | 1 | 1 | 1 | 0 | 1 |
| 12 | Juventus W | 1 | 1 | 2 | -1 | 0 |
| 13 | OH Leuven W | 1 | 0 | 0 | 0 | 1 |
| 14 | Roma W | 1 | 0 | 0 | 0 | 1 |
| 15 | Austria Wien W | 1 | 0 | 1 | -1 | 0 |
| 16 | Häcken | 1 | 0 | 1 | -1 | 0 |
| 17 | Køge | 1 | 0 | 1 | -1 | 0 |
| 18 | Servette Chênois W | 1 | 0 | 8 | -8 | 0 |
