Prediction Audit: Brumov vs Sokol Lanžhot Prediction, Odds & AI Betting Tips

Sep 27, 2026 - 08:15
0 1.28
1 1.32
xG Accuracy: 64%

AI correctly predicted the Sokol Lanžhot win.

The match finished 0–1, 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 Under 2.5 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Sokol Lanžhot Sokol Lanžhot ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Sokol Lanžhot higher than the statistical model.

Largest probability gap: Sokol Lanžhot -15.4 pp

Outcome Model Closing Market Difference Signal
Brumov 34.2% 23.3% +11.0 pp Model Edge
Draw 29.6% 25.2% +4.5 pp Aligned
Sokol Lanžhot 36.1% 51.5% -15.4 pp Market Higher

The closing market estimates Sokol Lanžhot's win probability at 51.5%, compared with the model's estimate of 36.1%, a difference of 15.4 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 (Sokol Lanžhot win 0–1).

Market Assessment

The market is materially more optimistic about Sokol Lanžhot 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

  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile
  • Exact score 0–1 fell within the model's highlighted bins

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Sokol Lanžhot higher (51.5% vs model 36.1%, 15.4 pp), but the model's lean was validated (Sokol Lanžhot win 0–1).

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Prediction Timeline

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

  1. Sep 27, 2026 · 08:14 UTC Forecast generated
    • Model 1X2 · Brumov 34.2% · Draw 29.7% · Sokol Lanžhot 36.1%
    • xG · Brumov 1.28 — Sokol Lanžhot 1.32
  2. Sep 27, 2026 · 07:44 UTC Opening odds snapshot PRE30
    • 1X2 odds · Brumov 3.81 · Draw 3.52 · Sokol Lanžhot 1.72
    • Implied 1X2 · Brumov 23.3% · Draw 25.2% · Sokol Lanžhot 51.5%
    • Bookmaker · Pinnacle
  3. Sep 27, 2026 · 08:14 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Brumov 3.81 · Draw 3.52 · Sokol Lanžhot 1.72
    • Implied 1X2 · Brumov 23.3% · Draw 25.2% · Sokol Lanžhot 51.5%
    • Bookmaker · Pinnacle
  4. Sep 27, 2026 · 08:15 UTC Kickoff
  5. FT Full-time result Sokol Lanžhot win · 0–1
  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: Monitor
Historical Decision Monitor
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 55/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 22/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 21, 2026 · 00:51 UTC Snapshot ID: dp-10080259

Closing Odds 1.72
AI Fair Odds —
CLV Pending
Final Result Sokol Lanžhot win · Brumov 0–1 Sokol Lanžhot
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

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: 4. liga - Divizie E
  • Fixture: Brumov vs Sokol Lanžhot
  • Kickoff: 2026-09-27 08:15:00
  • 1X2 (model): Home 34.2% · Draw 29.7% · Away 36.1%
  • xG (showing): Brumov 1.28 — Sokol Lanžhot 1.32 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • 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 No (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

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.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

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 30, 2026 (UTC)

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4. liga - Divizie E 4. liga - Divizie E — Standings
# TEAM MP W D L PTS
1 Kozlovice 8 6 2 0 20
2 Strání 7 6 1 0 19
3 Tatran Všechovice 7 6 0 1 18
4 SK Krumvir 7 6 0 1 18
5 Břeclav 8 4 2 2 14
6 Hluk 8 3 4 1 13
7 Sokol Lanžhot 7 4 0 3 12
8 Prostejov B 8 3 3 2 12
9 Holešov 8 2 4 2 10
10 Šternberk 8 3 1 4 10
11 Slavičín 8 3 1 4 10
12 Kroměříž II 7 1 2 4 5
13 Brumov 7 1 1 5 4
14 Nové Sady 8 1 1 6 4
15 Bzenec 8 1 0 7 3
16 Baťov 8 0 0 8 0
# TEAM MP GS GC +/- PTS
1 Strání 7 29 11 +18 19
2 Tatran Všechovice 7 26 8 +18 18
3 Kozlovice 8 22 7 +15 20
4 Hluk 8 20 11 +9 13
5 Prostejov B 8 16 16 0 12
6 SK Krumvir 7 15 7 +8 18
7 Holešov 8 15 12 +3 10
8 Šternberk 8 15 15 0 10
9 Slavičín 8 14 15 -1 10
10 Břeclav 8 13 8 +5 14
11 Sokol Lanžhot 7 12 11 +1 12
12 Bzenec 8 12 28 -16 3
13 Brumov 7 11 25 -14 4
14 Nové Sady 8 10 33 -23 4
15 Kroměříž II 7 7 13 -6 5
16 Baťov 8 7 24 -17 0