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

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

Al Riyadh Al Riyadh
May 10, 2026 - 16:05
1 1.80
0 1.86
xG Accuracy: 48%
Al-Fateh Al-Fateh

The model missed the final outcome (Al Riyadh win 1–0).

The model had projected Al-Fateh at 39.2%, 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 (1 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Al-Fateh Al Riyadh ✖ Incorrect
  • Correct Score Insights 1-1, 1-2, 2-1, 2-2, 1-3 1-0 ✖ Incorrect

Model vs Closing Market

Moderate Disagreement

The model rates Al-Fateh considerably stronger than the closing betting market.

Largest probability gap: Al-Fateh +8.4 pp

Outcome Model Closing Market Difference Signal
Al Riyadh 36.8% 43.2% -6.4 pp Market Higher
Draw 24.0% 26.0% -2.0 pp Aligned
Al-Fateh 39.2% 30.8% +8.4 pp Model Higher

The statistical model estimates Al-Fateh's win probability at 39.2%, compared with the closing market's implied probability of 30.8%, a difference of 8.4 percentage points. This highlights a substantial disagreement between the model's assessment and the market consensus, rather than 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 Al Riyadh win 1–0.

Market Assessment

The fair estimate shows a modest edge over current market pricing on Al-Fateh.

  • 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 (1 goals)

Market lesson

The closing market differed from the model on Al-Fateh by 8.4 percentage points (30.8% vs model 39.2%) — 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 07, 2026 · 16:59 UTC Forecast generated
    • Model 1X2 · Al Riyadh 36.8% · Draw 24.0% · Al-Fateh 39.2%
    • xG · Al Riyadh 1.80 — Al-Fateh 1.86
  2. May 07, 2026 · 16:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al Riyadh 2.17 · Draw 3.60 · Al-Fateh 3.04
    • Implied 1X2 · Al Riyadh 43.2% · Draw 26.0% · Al-Fateh 30.8%
    • Bookmaker · Pinnacle
  3. May 07, 2026 · 16:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al Riyadh 2.17 · Draw 3.60 · Al-Fateh 3.04
    • Implied 1X2 · Al Riyadh 43.2% · Draw 26.0% · Al-Fateh 30.8%
    • Bookmaker · Pinnacle
  4. May 10, 2026 · 16:05 UTC Kickoff
  5. FT Full-time result Al Riyadh win · 1–0
  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 75/100 · High
  • Validation: Pass
Evidence ★★★★★
  • Statistical edge detected
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 19/100
Monitoring Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 27, 2026 · 15:00 UTC Snapshot ID: dp-2040808

Closing Odds 3.04
AI Fair Odds —
CLV Pending
Final Result Al Riyadh win · Al Riyadh 1–0 Al-Fateh
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: Pro League
  • Fixture: Al Riyadh vs Al-Fateh
  • Kickoff: 2026-05-07 17:00:00
  • 1X2 (model): Home 36.8% · Draw 24.0% · Away 39.2%
  • xG (showing): Al Riyadh 1.8 — Al-Fateh 1.86 (total xG ≈ 3.66)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 70.8% · Implied: 57.0% · Probability edge: +13.8 pts · Est. EV: +20.4%
  • BTTS (model): Yes 71.6% · No 28.4%
  • Correct score (top bin): 1-1 (8.6%)

Totals and BTTS are evaluated against current market prices where available.

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

September 30, 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