Prediction Audit: Viborg vs Aarhus Prediction, Odds & AI Betting Tips

Aug 14, 2026 - 17:00
2 1.79
1 1.32
xG Accuracy: 86%

AI correctly predicted the Viborg win.

The match finished 2–1, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade A

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Viborg Viborg ✔ Correct
  • Correct Score Insights 1-1, 2-1, 1-0, 2-0, 1-2 2-1 ✔ Correct

Model vs Closing Market

Broadly Aligned

The model and closing market are broadly aligned.

Largest probability gap: Aarhus -0.5 pp

Outcome Model Closing Market Difference Signal
Viborg 47.0% 46.7% +0.2 pp Aligned
Draw 25.8% 25.5% +0.3 pp Aligned
Aarhus 27.2% 27.7% -0.5 pp Aligned

The model and closing market are broadly aligned, with probability differences below 5 percentage points.

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 model's directional lean matched the result (Viborg win 2–1).

Market Assessment

The market and model are broadly aligned. Any small pricing gap likely reflects rounding or bookmaker margin, not a structural disagreement.

  • Current pricing remains close to the model baseline.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 3.11) — 3 goals materialised
  • Viborg attacking xG significantly stronger (1.79 vs 1.32)
  • Both Teams To Score (Yes) matched the full-time result

Market lesson

The model's directional lean matched the full-time result (Viborg win 2–1).

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Prediction Timeline

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

  1. Aug 14, 2026 · 19:18 UTC Forecast generated
    • Model 1X2 · Viborg 47.0% · Draw 25.8% · Aarhus 27.3%
    • xG · Viborg 1.79 — Aarhus 1.32
  2. Aug 14, 2026 · 16:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · Viborg 2.07 · Draw 3.79 · Aarhus 3.49
    • Implied 1X2 · Viborg 46.7% · Draw 25.5% · Aarhus 27.7%
    • Bookmaker · Pinnacle
  3. Aug 14, 2026 · 16:56 UTC Closing snapshot recorded PRE5
    • 1X2 odds · Viborg 2.07 · Draw 3.79 · Aarhus 3.49
    • Implied 1X2 · Viborg 46.7% · Draw 25.5% · Aarhus 27.7%
    • Bookmaker · Pinnacle
  4. Aug 14, 2026 · 17:00 UTC Kickoff
  5. FT Full-time result Viborg win · 2–1
  6. FT Prediction validated Directional lean matched full-time result
  7. Archived Prediction review

Historical Snapshot

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

Historical verdict: Observe
Historical Decision No Primary Bet
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 79/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Market Compatibility 97/100
Betting Confidence 82/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 08, 2026 · 01:35 UTC Snapshot ID: dp-3229616

Closing Odds 3.49
AI Fair Odds —
CLV Pending
Final Result Viborg win · Viborg 2–1 Aarhus
Prediction ✔ Correct
Decision Grade A

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

Quick read on how the model reads this matchup.

  • League: Superliga
  • Fixture: Viborg vs Aarhus
  • Kickoff: 2026-08-14 17:00:00
  • 1X2 (model): Home 35.0% · Draw 35.0% · Away 30.0%
  • xG (showing): Viborg 1.79 — Aarhus 1.32 (total xG ≈ 3.11)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

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

Historical Recommendation

Historical Decision: No Primary Bet

Outcome: Validated — Pre-match lean validated against 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 28, 2026 (UTC)

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Superliga Superliga — Standings
# TEAM MP W D L PTS
1 FC Copenhagen 9 8 0 1 24
2 FC Midtjylland 9 5 4 0 19
3 Viborg 9 5 2 2 17
4 FC Nordsjaelland 9 5 2 2 17
5 Brondby 9 4 1 4 13
6 AC Horsens 9 3 2 4 11
7 Silkeborg 9 2 4 3 10
8 Randers FC 9 3 1 5 10
9 Odense 9 2 3 4 9
10 Lyngby 9 1 4 4 7
11 Aarhus 9 0 5 4 5
12 Sonderjyske 9 1 2 6 5
# TEAM MP GS GC +/- PTS
1 FC Copenhagen 9 23 8 +15 24
2 FC Midtjylland 9 17 9 +8 19
3 Viborg 9 15 8 +7 17
4 AC Horsens 9 15 16 -1 11
5 FC Nordsjaelland 9 14 10 +4 17
6 Silkeborg 9 12 12 0 10
7 Brondby 9 12 15 -3 13
8 Sonderjyske 9 12 21 -9 5
9 Randers FC 9 11 14 -3 10
10 Aarhus 9 11 17 -6 5
11 Lyngby 9 10 16 -6 7
12 Odense 9 8 14 -6 9
# TEAM MP xG xGC +/- PTS
1 FC Nordsjaelland 9 15.9 7.0 +8.9 17
2 Lyngby 9 12.2 8.1 +4.1 7
3 Viborg 9 9.7 6.4 +3.3 17
4 FC Midtjylland 9 9.3 6.3 +3.0 19
5 Aarhus 9 8.5 6.3 +2.2 5
6 FC Copenhagen 9 6.6 6.3 +0.3 24
7 Brondby 9 8.9 9.8 -0.9 13
8 Odense 9 8.7 9.7 -1.0 9
9 Silkeborg 9 6.2 9.8 -3.6 10
10 AC Horsens 9 7.3 11.3 -4.0 11
11 Randers FC 9 5.8 11.6 -5.8 10
12 Sonderjyske 9 5.9 12.2 -6.3 5