Predictions / Football / Qatar. QSL Cup / Al Waab vs Lusail City

Prediction Audit: Al Waab vs Lusail City Prediction, Odds & AI Betting Tips

Sep 29, 2026 - 17:15
1 1.36
1 1.24
xG Accuracy: 85%

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

The model had projected Al Waab at 38.0%, 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 Al Waab Draw ✖ Incorrect
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 1-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Lusail City higher than the statistical model.

Largest probability gap: Lusail City -15.0 pp

Outcome Model Closing Market Difference Signal
Al Waab 38.0% 27.9% +10.1 pp Model Edge
Draw 29.6% 24.7% +4.9 pp Aligned
Lusail City 32.4% 47.4% -15.0 pp Market Higher

The closing market estimates Lusail City's win probability at 47.4%, compared with the model's estimate of 32.4%, a difference of 15.0 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 is materially more optimistic about Lusail City 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 Al Waab; match finished Draw

Market lesson

The closing market differed from the model on Al Waab by 15.0 percentage points (53.0% vs model 38.0%) — 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 29, 2026 · 17:14 UTC Forecast generated
    • Model 1X2 · Al Waab 38.0% · Draw 29.6% · Lusail City 32.4%
    • xG · Al Waab 1.36 — Lusail City 1.24
  2. Sep 29, 2026 · 16:44 UTC Opening odds snapshot PRE30
    • 1X2 odds · Al Waab 3.24 · Draw 3.67 · Lusail City 1.91
    • Implied 1X2 · Al Waab 27.9% · Draw 24.7% · Lusail City 47.4%
    • Bookmaker · Pinnacle
  3. Sep 29, 2026 · 17:14 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Al Waab 3.24 · Draw 3.67 · Lusail City 1.91
    • Implied 1X2 · Al Waab 27.9% · Draw 24.7% · Lusail City 47.4%
    • Bookmaker · Pinnacle
  4. Sep 29, 2026 · 17:15 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 56/100 · Moderate
  • Validation: Warning
  • Large market gap (15 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 8/100
Monitoring Confidence 19/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 23, 2026 · 02:08 UTC Snapshot ID: dp-10419947

Closing Odds 1.91
AI Fair Odds —
CLV Pending
Final Result Draw · Al Waab 1–1 Lusail City
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: QSL Cup
  • Fixture: Al Waab vs Lusail City
  • Kickoff: 2026-09-29 17:15:00
  • 1X2 (model): Home 38.0% · Draw 29.6% · Away 32.4%
  • xG (showing): Al Waab 1.36 — Lusail City 1.24 (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: 46.7% · Probability edge: +5.1 pts · Est. EV: +7.2%
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

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

1X2 can look balanced even when side markets show clearer structure.

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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