Predictions / Football / Denmark. DBU Pokalen / Skive vs Esbjerg

Prediction Audit: Skive vs Esbjerg Prediction, Odds & AI Betting Tips

Skive Skive
Aug 25, 2026 - 17:00
1 1.34
5 1.26
xG Accuracy: 33%
Esbjerg Esbjerg

The model missed the final outcome (Esbjerg win 1–5).

The model had projected Skive at 37.1%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade F

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 (6 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Skive Esbjerg ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-5 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Esbjerg higher than the statistical model.

Largest probability gap: Esbjerg -21.6 pp

Outcome Model Closing Market Difference Signal
Skive 37.1% 21.0% +16.0 pp Model Edge
Draw 29.6% 24.0% +5.6 pp Model Higher
Esbjerg 33.3% 54.9% -21.6 pp Market Higher

The closing market estimates Esbjerg's win probability at 54.9%, compared with the model's estimate of 33.3%, a difference of 21.6 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 Esbjerg win 1–5.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 6 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 (6 goals)
  • 1X2: model leaned Skive; match finished Esbjerg

Market lesson

The closing market differed from the model on Skive by 21.6 percentage points (58.7% vs model 37.1%) — in this case the market view proved closer.

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Aug 25, 2026 · 16:59 UTC Forecast generated
    • Model 1X2 · Skive 37.0% · Draw 29.6% · Esbjerg 33.4%
    • xG · Skive 1.34 — Esbjerg 1.26
  2. Aug 25, 2026 · 16:30 UTC Opening odds snapshot PRE30
    • 1X2 odds · Skive 4.31 · Draw 3.77 · Esbjerg 1.65
    • Implied 1X2 · Skive 21.0% · Draw 24.0% · Esbjerg 54.9%
    • Bookmaker · Pinnacle
  3. Aug 25, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Skive 4.31 · Draw 3.77 · Esbjerg 1.65
    • Implied 1X2 · Skive 21.0% · Draw 24.0% · Esbjerg 54.9%
    • Bookmaker · Pinnacle
  4. Aug 25, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Esbjerg win · 1–5
  6. FT Prediction missed 1X2 lean did not match full-time result
  7. Archived Prediction review

Historical Snapshot

Frozen at kickoff — the model output as it stood before the match started.

Historical verdict: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 52/100 · Moderate
  • Validation: Warning
  • Large market gap (22 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 14/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 19, 2026 · 02:26 UTC Snapshot ID: dp-4551985

Closing Odds 1.65
AI Fair Odds —
CLV Pending
Final Result Esbjerg win · Skive 1–5 Esbjerg
Prediction ✖ Missed
Decision Grade F

Model 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.

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: DBU Pokalen
  • Fixture: Skive vs Esbjerg
  • Kickoff: 2026-08-25 17:00:00
  • 1X2 (model): Home 37.0% · Draw 29.6% · Away 33.4%
  • xG (showing): Skive 1.34 — Esbjerg 1.26 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.1%, still below the +2.0% minimum for a headline / default stake (no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: Wait

Outcome: Missed — Pre-match 1X2 lean did not match the full-time result.

Risk Factors Considered Before Kickoff

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Last Updated

September 29, 2026 (UTC)

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