The model missed the final outcome (Vendsyssel FF win 1–0).
The model had projected Hillerød 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 Under 2.5 (1 goals) ✔ Correct
- Both Teams To Score BTTS Yes No ✖ Incorrect
- 1X2 Hillerød Vendsyssel FF ✖ 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 |
|---|---|---|---|---|
| Vendsyssel FF | 32.4% | 42.4% | -10.0 pp | Market Higher |
| Draw | 29.6% | 26.4% | +3.2 pp | Aligned |
| Hillerød | 38.0% | 31.3% | +6.7 pp | Model Higher |
The closing market estimates Vendsyssel FF's win probability at 42.4%, compared with the model's estimate of 32.4%, a difference of 10.0 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 Vendsyssel FF win 1–0.
Market Assessment
The market is materially more optimistic about Vendsyssel FF 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
- 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
- 1X2: model leaned Hillerød; match finished Vendsyssel FF
Market lesson
The closing market differed from the model on Hillerød by 10.0 percentage points (48.0% vs model 38.0%) — in this case the market view proved closer.
Prediction Timeline
How this prediction moved from forecast to full-time review.
-
Aug 20, 2026 · 16:59 UTC Forecast generated
- Model 1X2 · Vendsyssel FF 32.4% · Draw 29.6% · Hillerød 38.0%
- xG · Vendsyssel FF 1.24 — Hillerød 1.36
-
Aug 20, 2026 · 16:29 UTC Opening odds snapshot PRE30
- 1X2 odds · Vendsyssel FF 2.25 · Draw 3.62 · Hillerød 3.05
- Implied 1X2 · Vendsyssel FF 42.4% · Draw 26.4% · Hillerød 31.3%
- Bookmaker · Pinnacle
-
Aug 20, 2026 · 16:59 UTC Closing snapshot recorded PRE1
- 1X2 odds · Vendsyssel FF 2.25 · Draw 3.62 · Hillerød 3.05
- Implied 1X2 · Vendsyssel FF 42.4% · Draw 26.4% · Hillerød 31.3%
- Bookmaker · Pinnacle
-
Aug 20, 2026 · 17:00 UTC Kickoff
-
FT Full-time result Vendsyssel FF 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: Warning
- Large market gap (10 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 |
