Predictions / Football / Saudi-Arabia. Pro League / Al Kholood vs Al-Fateh

Prediction Audit: Al Kholood vs Al-Fateh Prediction, Odds & AI Betting Tips

Al Kholood Al Kholood
May 21, 2026 - 18:00
0 1.08
0 1.46
xG Accuracy: 50%
Al-Fateh Al-Fateh

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

The model had projected Al-Fateh at 44.2%, but the full-time result went the other way.

Tracked markets vs full-time result

Prediction grade C

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 No No ✔ Correct
  • 1X2 Al-Fateh Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-2, 1-0, 0-2 0-0 ✖ Incorrect

Model vs Closing Market

Strong Disagreement

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

Largest probability gap: Al Kholood -12.8 pp

Outcome Model Closing Market Difference Signal
Al Kholood 26.4% 39.2% -12.8 pp Market Higher
Draw 29.4% 24.4% +5.1 pp Model Higher
Al-Fateh 44.2% 36.5% +7.8 pp Model Higher

The closing market estimates Al Kholood's win probability at 39.2%, compared with the model's estimate of 26.4%, a difference of 12.8 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 Kholood 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

  • Both Teams To Score (No) matched the full-time result
  • Under 2.5 goals aligned with the xG profile

What failed

  • 1X2: model leaned Al-Fateh; match finished Draw
  • Exact score: outside the model's top score bins

Market lesson

The closing market differed from the model on Al-Fateh by 12.8 percentage points (57.0% vs model 44.2%) — 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. May 21, 2026 · 18:16 UTC Forecast generated
    • Model 1X2 · Al Kholood 26.4% · Draw 29.4% · Al-Fateh 44.2%
    • xG · Al Kholood 1.08 — Al-Fateh 1.46
  2. May 21, 2026 · 16:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al Kholood 2.43 · Draw 3.91 · Al-Fateh 2.61
    • Implied 1X2 · Al Kholood 39.2% · Draw 24.4% · Al-Fateh 36.5%
    • Bookmaker · Pinnacle
  3. May 21, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al Kholood 2.43 · Draw 3.91 · Al-Fateh 2.61
    • Implied 1X2 · Al Kholood 39.2% · Draw 24.4% · Al-Fateh 36.5%
    • Bookmaker · Pinnacle
  4. May 21, 2026 · 18:00 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 57/100 · Moderate
  • Validation: Warning
  • Large market gap (13 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 12/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 18, 2026 · 22:24 UTC Snapshot ID: dp-4534514

Closing Odds 2.43
AI Fair Odds —
CLV Pending
Final Result Draw · Al Kholood 0–0 Al-Fateh
Prediction ✖ Missed
Decision Grade C

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: Pro League
  • Fixture: Al Kholood vs Al-Fateh
  • Kickoff: 2026-05-21 17:00:00
  • 1X2 (model): Home 26.4% · Draw 29.4% · Away 44.2%
  • xG (showing): Al Kholood 1.08 — Al-Fateh 1.46 (total xG ≈ 2.54)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 47.7% · Implied: 36.4% · Probability edge: +11.3 pts · Est. EV: +25.4%
  • BTTS (model): Yes 52.3% · No 47.7%
  • Correct score (top bin): 1-1 (12.4%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Early match state can move realised goals away from pre-kick projections.

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

October 02, 2026 (UTC)

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Pro League Pro League — Standings
# TEAM MP W D L PTS
1 Al-Nassr 34 28 2 4 86
2 Al-Hilal Saudi FC 34 25 9 0 84
3 Al-Ahli Jeddah 34 25 6 3 81
4 Al-Qadisiyah FC 34 23 8 3 77
5 Al-Ittihad FC 34 16 7 11 55
6 Al Taawon 34 15 8 11 53
7 Al-Ettifaq 34 14 8 12 50
8 NEOM 34 12 9 13 45
9 Al-Hazm 34 11 9 14 42
10 Al-Fayha 34 10 8 16 38
11 Al-Fateh 34 9 10 15 37
12 Al Khaleej Saihat 34 10 7 17 37
13 Al Shabab 34 8 11 15 35
14 Al Kholood 34 9 6 19 33
15 Al Riyadh 34 7 9 18 30
16 Damac 34 6 11 17 29
17 Al Akhdoud 34 5 5 24 20
18 Al Najma 34 3 7 24 16
# TEAM MP GS GC +/- PTS
1 Al-Nassr 34 91 28 +63 86
2 Al-Hilal Saudi FC 34 85 27 +58 84
3 Al-Qadisiyah FC 34 83 34 +49 77
4 Al-Ahli Jeddah 34 71 25 +46 81
5 Al Taawon 34 59 46 +13 53
6 Al-Ittihad FC 34 55 48 +7 55
7 Al Khaleej Saihat 34 54 62 -8 37
8 Al-Ettifaq 34 51 55 -4 50
9 Al Shabab 34 44 57 -13 35
10 NEOM 34 43 48 -5 45
11 Al-Fayha 34 41 54 -13 38
12 Al-Fateh 34 41 55 -14 37
13 Al Kholood 34 39 61 -22 33
14 Al-Hazm 34 38 57 -19 42
15 Al Riyadh 34 35 63 -28 30
16 Damac 34 32 55 -23 29
17 Al Najma 34 32 76 -44 16
18 Al Akhdoud 34 27 70 -43 20
# TEAM MP xG xGC +/- PTS
1 Al-Nassr 34 69.8 26.0 +43.8 86
2 Al-Hilal Saudi FC 34 68.9 25.9 +43.0 84
3 Al-Ahli Jeddah 34 62.4 26.7 +35.7 81
4 Al-Qadisiyah FC 34 62.9 35.2 +27.7 77
5 Al-Ittihad FC 34 49.5 41.2 +8.3 55
6 NEOM 34 45.8 39.4 +6.4 45
7 Al Shabab 34 44.1 44.7 -0.6 35
8 Al Taawon 34 42.0 44.7 -2.7 53
9 Al Khaleej Saihat 34 42.6 46.3 -3.7 37
10 Al-Fateh 34 42.5 49.6 -7.1 37
11 Al Riyadh 34 41.4 50.5 -9.1 30
12 Al-Fayha 34 33.3 43.4 -10.1 38
13 Al-Hazm 34 34.1 47.4 -13.3 42
14 Damac 34 25.1 38.5 -13.4 29
15 Al-Ettifaq 34 39.0 56.5 -17.5 50
16 Al Kholood 34 33.2 51.5 -18.3 33
17 Al Najma 34 28.1 61.0 -32.9 16
18 Al Akhdoud 34 26.8 62.8 -36.0 20