Predictions / Football / Denmark. Superliga / Brondby vs Viborg

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

Brondby Brondby
Aug 02, 2026 - 14:00
1 1.22
0 1.37
xG Accuracy: 65%
Viborg Viborg

AI correctly predicted the Brondby win.

The match finished 1–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

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 Brondby Brondby ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-0 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Brondby higher than the statistical model.

Largest probability gap: Brondby -13.3 pp

Outcome Model Closing Market Difference Signal
Brondby 36.8% 50.1% -13.3 pp Market Higher
Draw 28.7% 24.9% +3.8 pp Aligned
Viborg 34.5% 25.0% +9.5 pp Model Higher

The closing market estimates Brondby's win probability at 50.1%, compared with the model's estimate of 36.8%, a difference of 13.3 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 (Brondby win 1–0).

Market Assessment

The market is materially more optimistic about Brondby 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

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Brondby higher (50.1% vs model 36.8%, 13.3 pp), but the model's lean was validated (Brondby win 1–0).

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Prediction Timeline

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

  1. Aug 02, 2026 · 19:15 UTC Forecast generated
    • Model 1X2 · Brondby 36.8% · Draw 28.7% · Viborg 34.5%
    • xG · Brondby 1.22 — Viborg 1.37
  2. Aug 02, 2026 · 13:31 UTC Opening odds snapshot PRE30
    • 1X2 odds · Brondby 1.93 · Draw 3.89 · Viborg 3.87
    • Implied 1X2 · Brondby 50.1% · Draw 24.9% · Viborg 25.0%
    • Bookmaker · Pinnacle
  3. Aug 02, 2026 · 14:01 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Brondby 1.93 · Draw 3.89 · Viborg 3.87
    • Implied 1X2 · Brondby 50.1% · Draw 24.9% · Viborg 25.0%
    • Bookmaker · Pinnacle
  4. Aug 02, 2026 · 14:00 UTC Kickoff
  5. FT Full-time result Brondby win · 1–0
  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: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 56/100 · Moderate
  • Validation: Warning
  • Large market gap (13 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 33/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 27, 2026 · 01:24 UTC Snapshot ID: dp-1948373

Closing Odds 1.93
AI Fair Odds —
CLV Pending
Final Result Brondby win · Brondby 1–0 Viborg
Prediction ✔ Correct
Decision Grade B-

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: Superliga
  • Fixture: Brondby vs Viborg
  • Kickoff: 2026-08-02 14:00:00
  • 1X2 (model): Home 10.0% · Draw 45.0% · Away 45.0%
  • xG (showing): Brondby 1.22 — Viborg 1.37 (total xG ≈ 2.59)
  • 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

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: Monitor

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 29, 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