AI correctly predicted the Hvidovre win.
The match finished 1–3, 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 Over 2.5 (4 goals) ✖ Incorrect
- Both Teams To Score BTTS Yes Yes ✔ Correct
- 1X2 Hvidovre Hvidovre ✔ Correct
- Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-3 ✖ Incorrect
Model vs Closing Market
| Outcome | Model | Closing Market | Difference | Signal |
|---|---|---|---|---|
| Hobro | 31.5% | 42.8% | -11.3 pp | Market Higher |
| Draw | 29.5% | 26.1% | +3.5 pp | Aligned |
| Hvidovre | 39.0% | 31.1% | +7.9 pp | Model Higher |
The closing market estimates Hobro's win probability at 42.8%, compared with the model's estimate of 31.5%, a difference of 11.3 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 model's directional lean matched the result (Hvidovre win 1–3).
Market Assessment
The market is materially more optimistic about Hobro 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) — 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)
- Exact score: outside the model's top score bins
Market lesson
Large model–market gaps do not automatically mean the market is right. Here the closing market priced Hvidovre higher (50.3% vs model 39.0%, 11.3 pp), but the model's lean was validated (Hvidovre win 1–3).
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Sep 04, 2026 · 15:59 UTC Forecast generated
- Model 1X2 · Hobro 31.5% · Draw 29.5% · Hvidovre 39.0%
- xG · Hobro 1.22 — Hvidovre 1.38
-
Sep 04, 2026 · 15:29 UTC Opening odds snapshot PRE30
- 1X2 odds · Hobro 2.23 · Draw 3.66 · Hvidovre 3.07
- Implied 1X2 · Hobro 42.8% · Draw 26.1% · Hvidovre 31.1%
- Bookmaker · Pinnacle
-
Sep 04, 2026 · 15:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Hobro 2.23 · Draw 3.66 · Hvidovre 3.07
- Implied 1X2 · Hobro 42.8% · Draw 26.1% · Hvidovre 31.1%
- Bookmaker · Pinnacle
-
Sep 04, 2026 · 16:00 UTC Kickoff
-
FT Full-time result Hvidovre win · 1–3
-
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 (11 pp)
- No strong statistical edge
- Market has already priced much of the edge
- 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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1. Division — Standings
| # | TEAM | MP | W | D | L | PTS |
|---|---|---|---|---|---|---|
| 1 | Hvidovre | 9 | 6 | 3 | 0 | 21 |
| 2 | Vejle | 9 | 5 | 4 | 0 | 19 |
| 3 | FC Fredericia | 9 | 3 | 5 | 1 | 14 |
| 4 | Aarhus Fremad | 9 | 3 | 4 | 2 | 13 |
| 5 | Aalborg | 9 | 3 | 4 | 2 | 13 |
| 6 | Hobro | 9 | 4 | 1 | 4 | 13 |
| 7 | Vendsyssel FF | 9 | 2 | 4 | 3 | 10 |
| 8 | AB Copenhagen | 9 | 2 | 3 | 4 | 9 |
| 9 | Hillerød | 9 | 2 | 3 | 4 | 9 |
| 10 | Kolding IF | 9 | 1 | 5 | 3 | 8 |
| 11 | HB Koge | 9 | 1 | 4 | 4 | 7 |
| 12 | Esbjerg | 9 | 1 | 2 | 6 | 5 |
| # | TEAM | MP | GS | GC | +/- | PTS |
|---|---|---|---|---|---|---|
| 1 | Vejle | 9 | 22 | 13 | +9 | 19 |
| 2 | Hvidovre | 9 | 18 | 9 | +9 | 21 |
| 3 | Hillerød | 9 | 13 | 14 | -1 | 9 |
| 4 | FC Fredericia | 9 | 12 | 6 | +6 | 14 |
| 5 | Hobro | 9 | 12 | 16 | -4 | 13 |
| 6 | AB Copenhagen | 9 | 11 | 10 | +1 | 9 |
| 7 | Aalborg | 9 | 11 | 11 | 0 | 13 |
| 8 | HB Koge | 9 | 11 | 17 | -6 | 7 |
| 9 | Aarhus Fremad | 9 | 10 | 9 | +1 | 13 |
| 10 | Kolding IF | 9 | 10 | 12 | -2 | 8 |
| 11 | Vendsyssel FF | 9 | 10 | 14 | -4 | 10 |
| 12 | Esbjerg | 9 | 10 | 19 | -9 | 5 |
