Prediction Audit: Kazma vs Al Sahel Prediction, Odds & AI Betting Tips

Sep 01, 2026 - 15:40
0 1.42
0 1.18
xG Accuracy: 49%

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

The model had projected Kazma at 40.9%, 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 Under 2.5 (0 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Kazma Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 0-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Kazma higher than the statistical model.

Largest probability gap: Kazma -16.3 pp

Outcome Model Closing Market Difference Signal
Kazma 40.9% 57.2% -16.3 pp Market Higher
Draw 29.4% 25.7% +3.7 pp Aligned
Al Sahel 29.7% 17.1% +12.5 pp Model Edge

The closing market estimates Kazma's win probability at 57.2%, compared with the model's estimate of 40.9%, a difference of 16.3 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 0–0.

Market Assessment

The market is materially more optimistic about Kazma 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

What failed

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

Market lesson

The closing market differed from the model on Kazma by 16.3 percentage points (57.2% vs model 40.9%) — 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 01, 2026 · 15:39 UTC Forecast generated
    • Model 1X2 · Kazma 41.0% · Draw 29.4% · Al Sahel 29.6%
    • xG · Kazma 1.42 — Al Sahel 1.18
  2. Sep 01, 2026 · 15:09 UTC Opening odds snapshot PRE30
    • 1X2 odds · Kazma 1.58 · Draw 3.52 · Al Sahel 5.27
    • Implied 1X2 · Kazma 57.2% · Draw 25.7% · Al Sahel 17.1%
    • Bookmaker · Pinnacle
  3. Sep 01, 2026 · 15:39 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Kazma 1.58 · Draw 3.52 · Al Sahel 5.27
    • Implied 1X2 · Kazma 57.2% · Draw 25.7% · Al Sahel 17.1%
    • Bookmaker · Pinnacle
  4. Sep 01, 2026 · 15:40 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: Monitor
Historical Decision Monitor
Outcome Missed
Pre-match metrics (historical context)
Prediction Reliability 55/100 · Moderate
  • Validation: Warning
  • Large market gap (16 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 18/100
Betting Confidence 44/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 24, 2026 · 02:12 UTC Snapshot ID: dp-5299350

Closing Odds 1.58
AI Fair Odds —
CLV Pending
Final Result Draw · Kazma 0–0 Al Sahel
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

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

  • League: Premier League
  • Fixture: Kazma vs Al Sahel
  • Kickoff: 2026-09-01 15:40:00
  • 1X2 (model): Home 41.0% · Draw 29.4% · Away 29.6%
  • xG (showing): Kazma 1.42 — Al Sahel 1.18 (total xG ≈ 2.6)
  • Value headline: None (actionable) — best tracked EV is about +1.1%, 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 54.1% · No 45.9%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.1% · No 45.9%
  • Correct score (top bin): 1-1 (12.4%)

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.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

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 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