Predictions / Football / Kuwait. Division 1 / Burgan vs Al Sulaibikhat

Prediction Audit: Burgan vs Al Sulaibikhat Prediction, Odds & AI Betting Tips

Burgan Burgan
Aug 07, 2026 - 17:45
0 1.24
0 1.60
xG Accuracy: 46%
Al Sulaibikhat Al Sulaibikhat

The model missed the final outcome (Draw 0–0).

The model had projected Al Sulaibikhat at 47.4%, 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 Over 2.5 Under 2.5 (0 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Al Sulaibikhat Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 0-2, 1-0 0-0 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The closing market prices Al Sulaibikhat higher than the statistical model.

Largest probability gap: Al Sulaibikhat -7.1 pp

Outcome Model Closing Market Difference Signal
Burgan 25.8% 20.1% +5.7 pp Model Higher
Draw 26.8% 25.4% +1.4 pp Aligned
Al Sulaibikhat 47.4% 54.5% -7.1 pp Market Higher

The closing market estimates Al Sulaibikhat's win probability at 54.5%, compared with the model's estimate of 47.4%, a difference of 7.1 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 Draw 0–0.

Market Assessment

The market and model broadly agree on Al Sulaibikhat. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No
  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (0 goals)

Market lesson

The closing market differed from the model on Al Sulaibikhat by 7.1 percentage points (54.5% vs model 47.4%) — 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 07, 2026 · 19:19 UTC Forecast generated
    • Model 1X2 · Burgan 25.8% · Draw 26.8% · Al Sulaibikhat 47.4%
    • xG · Burgan 1.24 — Al Sulaibikhat 1.60
  2. Aug 07, 2026 · 17:14 UTC Opening odds snapshot PRE30
    • 1X2 odds · Burgan 4.43 · Draw 3.49 · Al Sulaibikhat 1.63
    • Implied 1X2 · Burgan 20.1% · Draw 25.4% · Al Sulaibikhat 54.5%
    • Bookmaker · Pinnacle
  3. Aug 07, 2026 · 17:44 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Burgan 4.43 · Draw 3.49 · Al Sulaibikhat 1.63
    • Implied 1X2 · Burgan 20.1% · Draw 25.4% · Al Sulaibikhat 54.5%
    • Bookmaker · Pinnacle
  4. Aug 07, 2026 · 17:45 UTC Kickoff
  5. FT Full-time result Draw · 0–0
  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: Observe
Historical Decision No Primary Bet
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 64/100
Betting Confidence 78/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 31, 2026 · 02:11 UTC Snapshot ID: dp-2558450

Closing Odds 1.63
AI Fair Odds —
CLV Pending
Final Result Draw · Burgan 0–0 Al Sulaibikhat
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

Quick read on how the model reads this matchup.

  • League: Division 1
  • Fixture: Burgan vs Al Sulaibikhat
  • Kickoff: 2026-08-07 17:45:00
  • 1X2 (model): Home 25.8% · Draw 26.8% · Away 47.4%
  • xG (showing): Burgan 1.24 — Al Sulaibikhat 1.6 (total xG ≈ 2.84)
  • Value headline: None — no positive EV on tracked lines at current best prices (same as the decision block: no default bet).
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Over 2.5 (Under 2.5 46.0% · Over 2.5 54.0%); BTTS Yes (Yes 58.2% · No 41.8%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 58.2% · No 41.8%
  • Correct score (top bin): 1-1 (11.6%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

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

Historical Recommendation

Historical Decision: No Primary Bet

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

October 02, 2026 (UTC)

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Division 1 Division 1 — Standings
# TEAM MP W D L PTS
1 Al Sulaibikhat 21 13 5 3 44
2 Al Sahel 21 13 5 3 44
3 Yarmouk 21 13 4 4 43
4 Al Jazira 21 11 5 5 38
5 Khaitan 21 7 6 8 27
6 Burgan 21 5 8 8 23
7 Shamiya 21 3 1 17 10
8 Sporty 21 2 0 19 6
# TEAM MP GS GC +/- PTS
1 Yarmouk 21 42 20 +22 43
2 Al Jazira 21 41 24 +17 38
3 Al Sulaibikhat 21 38 16 +22 44
4 Al Sahel 21 35 16 +19 44
5 Burgan 21 26 30 -4 23
6 Khaitan 21 23 20 +3 27
7 Shamiya 21 19 63 -44 10
8 Sporty 21 14 49 -35 6