Predictions / Football / Qatar. Second Division / Al Waab vs Qatar U23

Prediction Audit: Al Waab vs Qatar U23 Prediction, Odds & AI Betting Tips

Sep 06, 2026 - 14:00
1 1.27
1 1.33
xG Accuracy: 85%

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

The model had projected Qatar U23 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 Under 2.5 Under 2.5 (2 goals) ✔ Correct
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Qatar U23 Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

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

Largest probability gap: Al Waab -12.3 pp

Outcome Model Closing Market Difference Signal
Al Waab 33.8% 46.1% -12.3 pp Market Higher
Draw 29.6% 24.9% +4.7 pp Aligned
Qatar U23 36.6% 29.0% +7.6 pp Model Higher

The closing market estimates Al Waab's win probability at 46.1%, compared with the model's estimate of 33.8%, a difference of 12.3 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: PRE5.

After full time, the result was Draw 1–1.

Market Assessment

The market is materially more optimistic about Al Waab 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
  • Exact score 1–1 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS No; match finished BTTS Yes
  • 1X2: model leaned Qatar U23; match finished Draw

Market lesson

The closing market differed from the model on Qatar U23 by 12.3 percentage points (48.9% 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 06, 2026 · 13:59 UTC Forecast generated
    • Model 1X2 · Al Waab 33.8% · Draw 29.6% · Qatar U23 36.6%
    • xG · Al Waab 1.27 — Qatar U23 1.33
  2. Sep 06, 2026 · 13:33 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al Waab 1.95 · Draw 3.60 · Qatar U23 3.10
    • Implied 1X2 · Al Waab 46.1% · Draw 24.9% · Qatar U23 29.0%
    • Bookmaker · Bet365
  3. Sep 06, 2026 · 13:59 UTC Closing snapshot recorded PRE5
    • 1X2 odds · Al Waab 1.95 · Draw 3.60 · Qatar U23 3.10
    • Implied 1X2 · Al Waab 46.1% · Draw 24.9% · Qatar U23 29.0%
    • Bookmaker · Bet365
  4. Sep 06, 2026 · 14:00 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 57/100 · Moderate
  • Validation: Warning
  • Large market gap (12 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market has already priced much of the edge
  • Validation warning
Pricing proximity (inverse gap) 13/100
Monitoring Confidence 20/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 31, 2026 · 07:29 UTC Snapshot ID: dp-6362156

Closing Odds 1.95
AI Fair Odds —
CLV Pending
Final Result Draw · Al Waab 1–1 Qatar U23
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: Second Division
  • Fixture: Al Waab vs Qatar U23
  • Kickoff: 2026-09-06 14:00:00
  • 1X2 (model): Home 33.8% · Draw 29.6% · Away 36.6%
  • xG (showing): Al Waab 1.27 — Qatar U23 1.33 (total xG ≈ 2.6)
  • Best +EV line (same label as hero card when Primary thresholds are not met): Under 2.5 goals
  • Model: 51.8% · Implied: 45.9% · Probability edge: +5.9 pts · Est. EV: +6.2%
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.5%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

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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Second Division Second Division — Standings
# TEAM MP W D L PTS
1 Al-Markhiya 3 3 0 0 9
2 Al Bidda SC 3 2 1 0 7
3 Al Waab 3 2 1 0 7
4 Muaither SC 3 2 0 1 6
5 Al Kharaitiyat 3 1 2 0 5
6 Al Mesaimeer 3 1 1 1 4
7 UMM Salal 3 1 1 1 4
8 Al-Khor 3 1 0 2 3
9 Qatar U23 3 0 2 1 2
10 Al-Gharafa B 3 0 1 2 1
11 Al Shamal II 3 0 1 2 1
12 Al Rayyan SC B 3 0 0 3 0
# TEAM MP GS GC +/- PTS
1 Al-Markhiya 3 8 0 +8 9
2 Al Bidda SC 3 6 1 +5 7
3 Muaither SC 3 6 2 +4 6
4 Al-Khor 3 6 7 -1 3
5 Al Waab 3 4 1 +3 7
6 Al Kharaitiyat 3 4 2 +2 5
7 UMM Salal 3 4 7 -3 4
8 Al Mesaimeer 3 3 3 0 4
9 Qatar U23 3 2 4 -2 2
10 Al-Gharafa B 3 1 5 -4 1
11 Al Rayyan SC B 3 1 8 -7 0
12 Al Shamal II 3 0 5 -5 1