Predictions / Football / Kuwait. Premier League / Al Arabi vs Al Sulaibikhat

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

Sep 04, 2026 - 17:50
3 1.46
3 1.14
xG Accuracy: 39%

The model missed the final outcome (Draw 3–3).

The model had projected Al Arabi at 42.9%, 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 Over 2.5 (6 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Al Arabi Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 3-3 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

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

Largest probability gap: Al Arabi -34.3 pp

Outcome Model Closing Market Difference Signal
Al Arabi 42.9% 77.1% -34.3 pp Market Higher
Draw 29.2% 15.4% +13.8 pp Model Edge
Al Sulaibikhat 27.9% 7.4% +20.5 pp Model Edge

The closing market estimates Al Arabi's win probability at 77.1%, compared with the model's estimate of 42.9%, a difference of 34.3 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 result was Draw 3–3.

Post Match Insights

What worked

  • Expected goals projected a high-scoring match (ΣxG 2.60) — 6 goals materialised
  • Both Teams To Score (Yes) matched the full-time result

What failed

  • Over / Under 2.5: model leaned Under 2.5; match finished Over 2.5 (6 goals)
  • 1X2: model leaned Al Arabi; match finished Draw

Market lesson

The closing market differed from the model on Al Arabi by 34.3 percentage points (77.2% vs model 42.9%) — 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. Sep 04, 2026 · 17:49 UTC Forecast generated
    • Model 1X2 · Al Arabi 42.9% · Draw 29.2% · Al Sulaibikhat 27.9%
    • xG · Al Arabi 1.46 — Al Sulaibikhat 1.14
  2. Sep 04, 2026 · 17:19 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al Arabi 1.17 · Draw 5.84 · Al Sulaibikhat 12.16
    • Implied 1X2 · Al Arabi 77.1% · Draw 15.4% · Al Sulaibikhat 7.4%
    • Bookmaker · Pinnacle
  3. Sep 04, 2026 · 17:49 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al Arabi 1.17 · Draw 5.84 · Al Sulaibikhat 12.16
    • Implied 1X2 · Al Arabi 77.1% · Draw 15.4% · Al Sulaibikhat 7.4%
    • Bookmaker · Pinnacle
  4. Sep 04, 2026 · 17:50 UTC Kickoff
  5. FT Full-time result Draw · 3–3
  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: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 32/100 · Low
  • Validation: Fail
  • Large market gap (34 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation failed
Pricing proximity (inverse gap) 0/100
Monitoring Confidence 9/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 29, 2026 · 02:29 UTC Snapshot ID: dp-5923170

Closing Odds 1.17
AI Fair Odds —
CLV Pending
Final Result Draw · Al Arabi 3–3 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

Model favours Al Arabi; market prices Al Arabi instead — inputs may be missing or stale.

  • Model: Al Arabi 1.46 xG vs Al Sulaibikhat 1.14 → Al Arabi 42.9%
  • Market: Al Arabi ~77.1% implied
  • Validation failed — do not treat 1X2 EV as actionable.

Do not act on 1X2 value until validation passes. Structural leans (O/U, BTTS) need separate odds review.

Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 53.8% · No 46.2%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes

Historical Recommendation

Historical Decision: Wait

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 29, 2026 (UTC)

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Premier League Premier League — Standings
# TEAM MP W D L PTS
1 Kazma 3 2 1 0 7
2 Al Kuwait 3 2 1 0 7
3 Al Qadsia 3 2 0 1 6
4 Al Salmiyah 3 2 0 1 6
5 Al Nasar 3 2 0 1 6
6 Al Shabab 3 1 1 1 4
7 Al Sahel 3 1 1 1 4
8 Al Fahaheel 3 1 0 2 3
9 Al Jahra 3 1 0 2 3
10 Al Arabi 3 0 2 1 2
11 Al Sulaibikhat 3 0 2 1 2
12 Al Tadhamon 3 0 0 3 0
# TEAM MP GS GC +/- PTS
1 Al Arabi 3 7 8 -1 2
2 Kazma 3 6 3 +3 7
3 Al Fahaheel 3 6 5 +1 3
4 Al Shabab 3 6 6 0 4
5 Al Qadsia 3 5 2 +3 6
6 Al Kuwait 3 5 3 +2 7
7 Al Salmiyah 3 4 2 +2 6
8 Al Nasar 3 4 5 -1 6
9 Al Jahra 3 4 5 -1 3
10 Al Sulaibikhat 3 4 5 -1 2
11 Al Tadhamon 3 2 9 -7 0
12 Al Sahel 3 1 1 0 4