Predictions / Football / Saudi-Arabia. Pro League / Al-Faisaly FC vs Al-Hazm

Prediction Audit: Al-Faisaly FC vs Al-Hazm Prediction, Odds & AI Betting Tips

Sep 05, 2026 - 15:50
0 1.37
0 1.52
xG Accuracy: 45%

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

The model had projected Al-Hazm at 39.5%, 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-Hazm Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 0-1, 2-1, 1-0 0-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

The closing market prices Al-Faisaly FC higher than the statistical model.

Largest probability gap: Al-Faisaly FC -10.9 pp

Outcome Model Closing Market Difference Signal
Al-Faisaly FC 32.8% 43.6% -10.9 pp Market Higher
Draw 27.8% 27.3% +0.4 pp Aligned
Al-Hazm 39.5% 29.0% +10.5 pp Model Edge

The closing market estimates Al-Faisaly FC's win probability at 43.6%, compared with the model's estimate of 32.8%, a difference of 10.9 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 Al-Faisaly FC 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 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-Hazm by 10.9 percentage points (50.4% vs model 39.5%) — 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 05, 2026 · 15:49 UTC Forecast generated
    • Model 1X2 · Al-Faisaly FC 32.8% · Draw 27.8% · Al-Hazm 39.5%
    • xG · Al-Faisaly FC 1.37 — Al-Hazm 1.52
  2. Sep 05, 2026 · 15:19 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al-Faisaly FC 2.18 · Draw 3.48 · Al-Hazm 3.28
    • Implied 1X2 · Al-Faisaly FC 43.6% · Draw 27.3% · Al-Hazm 29.0%
    • Bookmaker · Pinnacle
  3. Sep 05, 2026 · 15:49 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al-Faisaly FC 2.18 · Draw 3.48 · Al-Hazm 3.28
    • Implied 1X2 · Al-Faisaly FC 43.6% · Draw 27.3% · Al-Hazm 29.0%
    • Bookmaker · Pinnacle
  4. Sep 05, 2026 · 15:50 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 58/100 · Moderate
  • Validation: Warning
  • Large market gap (11 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 15/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 30, 2026 · 03:37 UTC Snapshot ID: dp-6160410

Closing Odds 2.18
AI Fair Odds —
CLV Pending
Final Result Draw · Al-Faisaly FC 0–0 Al-Hazm
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: Pro League
  • Fixture: Al-Faisaly FC vs Al-Hazm
  • Kickoff: 2026-09-05 15:50:00
  • 1X2 (model): Home 32.8% · Draw 27.8% · Away 39.5%
  • xG (showing): Al-Faisaly FC 1.37 — Al-Hazm 1.52 (total xG ≈ 2.89)
  • 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 Over 2.5 (Under 2.5 44.8% · Over 2.5 55.2%); BTTS Yes (Yes 59.8% · No 40.2%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 59.8% · No 40.2%
  • 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: 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 28, 2026 (UTC)

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Pro League Pro League — Standings
# TEAM MP W D L PTS
1 Al-Hilal Saudi FC 7 6 0 1 18
2 Al-Ittihad FC 7 5 2 0 17
3 Al-Nassr 7 5 1 1 16
4 Al-Qadisiyah FC 7 5 1 1 16
5 NEOM 7 5 0 2 15
6 Al-Ahli Jeddah 7 4 0 3 12
7 Al Kholood 7 3 3 1 12
8 Al Diriyah 7 3 2 2 11
9 Al-Ettifaq 7 3 2 2 11
10 Al-Hazm 7 2 2 3 8
11 Al Riyadh 7 2 2 3 8
12 Al-Fayha 7 1 3 3 6
13 Al Khaleej Saihat 7 0 5 2 5
14 Al Shabab 7 0 4 3 4
15 Al-Fateh 7 0 3 4 3
16 Al-Faisaly FC 7 0 3 4 3
17 Al Taawon 7 0 3 4 3
18 Abha 7 0 2 5 2
# TEAM MP GS GC +/- PTS
1 Al-Hilal Saudi FC 7 23 5 +18 18
2 Al-Nassr 7 16 7 +9 16
3 Al-Qadisiyah FC 7 16 8 +8 16
4 Al-Ahli Jeddah 7 16 10 +6 12
5 NEOM 7 13 6 +7 15
6 Al-Ittihad FC 7 12 6 +6 17
7 Al Kholood 7 12 10 +2 12
8 Al-Ettifaq 7 11 11 0 11
9 Al Riyadh 7 8 16 -8 8
10 Al Diriyah 7 7 5 +2 11
11 Al-Hazm 7 7 9 -2 8
12 Al-Fayha 7 7 11 -4 6
13 Al Shabab 7 6 11 -5 4
14 Al-Faisaly FC 7 5 13 -8 3
15 Abha 7 5 13 -8 2
16 Al-Fateh 7 4 11 -7 3
17 Al Khaleej Saihat 7 3 10 -7 5
18 Al Taawon 7 3 12 -9 3
# TEAM MP xG xGC +/- PTS
1 Al-Hilal Saudi FC 7 13.7 4.9 +8.8 18
2 Al-Qadisiyah FC 7 9.1 3.6 +5.5 16
3 Al-Nassr 7 8.4 3.0 +5.4 16
4 Al Kholood 7 10.9 7.3 +3.6 12
5 Al-Ahli Jeddah 7 4.2 2.4 +1.8 12
6 Al-Ittihad FC 7 8.1 6.4 +1.7 17
7 Al-Ettifaq 7 6.7 5.7 +1.0 11
8 Al Diriyah 7 3.7 2.9 +0.8 11
9 Al Taawon 7 5.8 5.4 +0.4 3
10 NEOM 7 6.0 6.1 -0.1 15
11 Al Shabab 7 6.8 7.6 -0.8 4
12 Al-Fateh 7 4.5 6.9 -2.4 3
13 Al-Hazm 7 3.3 6.0 -2.7 8
14 Al Khaleej Saihat 7 4.2 7.2 -3.0 5
15 Abha 7 4.4 8.2 -3.8 2
16 Al Riyadh 7 3.4 8.5 -5.1 8
17 Al-Faisaly FC 7 4.5 9.7 -5.2 3
18 Al-Fayha 7 5.0 10.8 -5.8 6