Prediction Audit: Petrovac vs Bokelj Prediction, Odds & AI Betting Tips

Aug 01, 2026 - 18:00
0 1.36
1 1.24
xG Accuracy: 64%

The model missed the final outcome (Bokelj win 0–1).

The model had projected Petrovac at 38.0%, 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 Under 2.5 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Petrovac Bokelj ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 0-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Petrovac higher than the statistical model.

Largest probability gap: Petrovac -14.7 pp

Outcome Model Closing Market Difference Signal
Petrovac 38.0% 52.7% -14.7 pp Market Higher
Draw 29.6% 28.1% +1.5 pp Aligned
Bokelj 32.4% 19.2% +13.2 pp Model Edge

The closing market estimates Petrovac's win probability at 52.7%, compared with the model's estimate of 38.0%, a difference of 14.7 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 Bokelj win 0–1.

Market Assessment

The market is materially more optimistic about Petrovac 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 0–1 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • 1X2: model leaned Petrovac; match finished Bokelj

Market lesson

The closing market differed from the model on Petrovac by 14.7 percentage points (52.7% vs model 38.0%) — 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 01, 2026 · 18:03 UTC Forecast generated
    • Model 1X2 · Petrovac 38.0% · Draw 29.6% · Bokelj 32.4%
    • xG · Petrovac 1.36 — Bokelj 1.24
  2. Aug 01, 2026 · 17:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Petrovac 1.74 · Draw 3.27 · Bokelj 4.77
    • Implied 1X2 · Petrovac 52.7% · Draw 28.1% · Bokelj 19.2%
    • Bookmaker · Pinnacle
  3. Aug 01, 2026 · 18:03 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Petrovac 1.74 · Draw 3.27 · Bokelj 4.77
    • Implied 1X2 · Petrovac 52.7% · Draw 28.1% · Bokelj 19.2%
    • Bookmaker · Pinnacle
  4. Aug 01, 2026 · 18:00 UTC Kickoff
  5. FT Full-time result Bokelj win · 0–1
  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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 56/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 26/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 27, 2026 · 01:52 UTC Snapshot ID: dp-1954986

Closing Odds 1.74
AI Fair Odds —
CLV Pending
Final Result Bokelj win · Petrovac 0–1 Bokelj
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: First League
  • Fixture: Petrovac vs Bokelj
  • Kickoff: 2026-08-01 18:00:00
  • 1X2 (model): Home 38.0% · Draw 29.6% · Away 32.4%
  • xG (showing): Petrovac 1.36 — Bokelj 1.24 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.8%, 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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • 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.

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: 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 30, 2026 (UTC)

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Back to Predictions
First League First League — Standings
# TEAM MP W D L PTS
1 Otrant-Olympic 9 5 1 3 16
2 Dečić 9 4 3 2 15
3 Bokelj 9 4 3 2 15
4 Buducnost Podgorica 9 4 2 3 14
5 Sutjeska 9 4 2 3 14
6 Mornar 9 3 4 2 13
7 Mladost DG 9 3 1 5 10
8 Jezero 9 2 3 4 9
9 Petrovac 9 1 5 3 8
10 Arsenal Tivat 9 1 4 4 7
# TEAM MP GS GC +/- PTS
1 Otrant-Olympic 9 15 10 +5 16
2 Buducnost Podgorica 9 11 7 +4 14
3 Sutjeska 9 11 7 +4 14
4 Dečić 9 10 7 +3 15
5 Mornar 9 9 7 +2 13
6 Jezero 9 9 15 -6 9
7 Bokelj 9 8 5 +3 15
8 Mladost DG 9 8 15 -7 10
9 Petrovac 9 7 9 -2 8
10 Arsenal Tivat 9 5 11 -6 7