Prediction Audit: Al-Nahda vs Al Seeb Prediction, Odds & AI Betting Tips

Sep 10, 2026 - 14:55
1 1.27
1 1.33
xG Accuracy: 85%

The model missed the final outcome (Draw 1–1).

The model had projected Al Seeb at 36.6%, 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 (2 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Al Seeb Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-1 ✔ Correct

Model vs Closing Market

Moderate Disagreement

The closing market prices Draw higher than the statistical model.

Largest probability gap: Draw -7.0 pp

Outcome Model Closing Market Difference Signal
Al-Nahda 33.8% 27.1% +6.7 pp Model Higher
Draw 29.6% 36.7% -7.0 pp Market Higher
Al Seeb 36.6% 36.2% +0.4 pp Aligned

The closing market estimates Draw's win probability at 36.7%, compared with the model's estimate of 29.6%, a difference of 7.0 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 1–1.

Market Assessment

The market and model broadly agree on Draw. The remaining divergence may reflect differences in team-strength assumptions rather than a directional disagreement.

  • Monitor line movement before kickoff — not a betting recommendation.

Post Match Insights

What worked

  • Both Teams To Score (Yes) matched the full-time result
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • Over / Under 2.5: model leaned Over 2.5; match finished Under 2.5 (2 goals)
  • 1X2: model leaned Al Seeb; match finished Draw

Market lesson

The closing market differed from the model on Al Seeb by 7.0 percentage points (43.6% vs model 36.6%) — 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 10, 2026 · 14:54 UTC Forecast generated
    • Model 1X2 · Al-Nahda 33.8% · Draw 29.6% · Al Seeb 36.6%
    • xG · Al-Nahda 1.27 — Al Seeb 1.33
  2. Sep 10, 2026 · 14:24 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al-Nahda 3.38 · Draw 2.50 · Al Seeb 2.53
    • Implied 1X2 · Al-Nahda 27.1% · Draw 36.7% · Al Seeb 36.2%
    • Bookmaker · Pinnacle
  3. Sep 10, 2026 · 14:54 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al-Nahda 3.38 · Draw 2.50 · Al Seeb 2.53
    • Implied 1X2 · Al-Nahda 27.1% · Draw 36.7% · Al Seeb 36.2%
    • Bookmaker · Pinnacle
  4. Sep 10, 2026 · 14:55 UTC Kickoff
  5. FT Full-time result Draw · 1–1
  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 ★★★★★
  • No strong statistical edge
  • Direction agrees with model lean
  • Validation passed
Pricing proximity (inverse gap) 22/100
Monitoring Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 04, 2026 · 01:32 UTC Snapshot ID: dp-6848970

Closing Odds 2.5
AI Fair Odds —
CLV Pending
Final Result Draw · Al-Nahda 1–1 Al Seeb
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

Pre-match snapshot for this fixture.

  • League: Professional League
  • Fixture: Al-Nahda vs Al Seeb
  • Kickoff: 2026-09-10 14:55:00
  • 1X2 (model): Home 33.8% · Draw 29.6% · Away 36.6%
  • xG (showing): Al-Nahda 1.27 — Al Seeb 1.33 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Over 2.5 goals
  • Model: 48.2% · Implied: 44.5% · Probability edge: +3.7 pts · Est. EV: +3.6%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

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.

Correct score remains high-variance even when a line is most likely on paper.

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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Professional League Professional League — Standings
# TEAM MP W D L PTS
1 Al Seeb 3 2 1 0 7
2 Al-Nahda 3 2 1 0 7
3 Al Nasr 2 2 0 0 6
4 Al-Shabab 3 2 0 1 6
5 Oman Club 3 2 0 1 6
6 Saham 3 2 0 1 6
7 Sohar 3 1 2 0 5
8 Ibri 3 1 1 1 4
9 Smail 3 1 1 1 4
10 Bahla 3 1 0 2 3
11 Dhofar 3 0 1 2 1
12 Fanja 3 0 1 2 1
13 Al Musannah 2 0 0 2 0
14 Sur 3 0 0 3 0
# TEAM MP GS GC +/- PTS
1 Al-Shabab 3 7 5 +2 6
2 Al Seeb 3 6 2 +4 7
3 Ibri 3 5 2 +3 4
4 Al-Nahda 3 5 3 +2 7
5 Al Nasr 2 4 1 +3 6
6 Bahla 3 4 5 -1 3
7 Oman Club 3 3 2 +1 6
8 Saham 3 3 2 +1 6
9 Sur 3 3 8 -5 0
10 Sohar 3 1 0 +1 5
11 Smail 3 1 4 -3 4
12 Dhofar 3 1 4 -3 1
13 Al Musannah 2 0 2 -2 0
14 Fanja 3 0 3 -3 1