Predictions / Football / Uzbekistan. Super League / Nasaf vs Qizilqum

Prediction Audit: Nasaf vs Qizilqum Prediction, Odds & AI Betting Tips

Nasaf Nasaf
Jul 28, 2026 - 15:00
1 1.48
0 1.12
xG Accuracy: 64%
Qizilqum Qizilqum

AI correctly predicted the Nasaf win.

The match finished 1–0, validating the model's directional assessment.

Tracked markets vs full-time result

Prediction grade B-

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 (1 goals) ✔ Correct
  • Both Teams To Score BTTS Yes No ✖ Incorrect
  • 1X2 Nasaf Nasaf ✔ Correct
  • Correct Score Insights 1-1, 1-0, 2-1, 0-1, 2-0 1-0 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Nasaf higher than the statistical model.

Largest probability gap: Nasaf -12.1 pp

Outcome Model Closing Market Difference Signal
Nasaf 48.4% 60.5% -12.1 pp Market Higher
Draw 28.4% 24.2% +4.2 pp Aligned
Qizilqum 23.2% 15.3% +8.0 pp Model Higher

The closing market estimates Nasaf's win probability at 60.5%, compared with the model's estimate of 48.4%, a difference of 12.1 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 model's directional lean matched the result (Nasaf win 1–0).

Market Assessment

The market is materially more optimistic about Nasaf 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

  • Nasaf attacking xG significantly stronger (1.48 vs 1.12)
  • Under 2.5 goals aligned with the xG profile
  • Exact score 1–0 fell within the model's highlighted bins

What failed

  • Both Teams To Score: model leaned BTTS Yes; match finished BTTS No

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Nasaf higher (60.5% vs model 48.4%, 12.1 pp), but the model's lean was validated (Nasaf win 1–0).

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Prediction Timeline

How this prediction moved from forecast to full-time review.

  1. Jul 28, 2026 · 19:14 UTC Forecast generated
    • Model 1X2 · Nasaf 48.4% · Draw 28.4% · Qizilqum 23.2%
    • xG · Nasaf 1.48 — Qizilqum 1.12
  2. Jul 28, 2026 · 14:29 UTC Opening odds snapshot PRE30
    • 1X2 odds · Nasaf 1.53 · Draw 3.83 · Qizilqum 6.07
    • Implied 1X2 · Nasaf 60.5% · Draw 24.2% · Qizilqum 15.3%
    • Bookmaker · Pinnacle
  3. Jul 28, 2026 · 14:59 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Nasaf 1.53 · Draw 3.83 · Qizilqum 6.07
    • Implied 1X2 · Nasaf 60.5% · Draw 24.2% · Qizilqum 15.3%
    • Bookmaker · Pinnacle
  4. Jul 28, 2026 · 15:00 UTC Kickoff
  5. FT Full-time result Nasaf win · 1–0
  6. FT Prediction validated Directional lean matched 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 Validated
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) 39/100
Betting Confidence 45/100

Validation Report

Immutable Snapshot

Prediction Time: Jul 23, 2026 · 13:50 UTC Snapshot ID: dp-1451727

Closing Odds 1.53
AI Fair Odds —
CLV Pending
Final Result Nasaf win · Nasaf 1–0 Qizilqum
Prediction ✔ Correct
Decision Grade B-

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: Super League
  • Fixture: Nasaf vs Qizilqum
  • Kickoff: 2026-07-28 15:00:00
  • 1X2 (model): Home 45.0% · Draw 45.0% · Away 10.0%
  • xG (showing): Nasaf 1.48 — Qizilqum 1.12 (total xG ≈ 2.6)
  • Value headline: None — no positive EV could be estimated on tracked lines at current best prices (missing odds or thin book depth).
  • Structural leans (not bets): See the Over/Under and BTTS cards for any directional lean text.
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

When book depth is thin or odds are missing, EV may be unavailable even though the model still prefers one side on totals or BTTS — wait for cleaner prices or skip.

Most likely correct score stays a low-probability tail: use it for context, not as a must-bet story.

Historical Recommendation

Historical Decision: Monitor

Outcome: Validated — Pre-match lean validated against 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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Super League Super League — Standings
# TEAM MP W D L PTS
1 Neftchi 22 16 3 3 51
2 Pakhtakor 22 14 7 1 49
3 Navbahor 22 13 5 4 44
4 Olmaliq 22 10 5 7 35
5 Lokomotiv 22 10 5 7 35
6 Nasaf 22 9 7 6 34
7 Buxoro 22 10 4 8 34
8 Andijan 22 9 3 10 30
9 Dinamo Samarqand 22 8 6 8 30
10 Qizilqum 22 9 2 11 29
11 Sogdiana 22 8 4 10 28
12 Surkhon 22 7 5 10 26
13 Bunyodkor 22 7 1 14 22
14 Xorazm 22 5 6 11 21
15 Kokand-1912 22 4 8 10 20
16 Mash'al 22 1 1 20 4
# TEAM MP GS GC +/- PTS
1 Neftchi 22 50 17 +33 51
2 Pakhtakor 22 39 20 +19 49
3 Navbahor 22 39 21 +18 44
4 Sogdiana 22 38 43 -5 28
5 Lokomotiv 22 36 28 +8 35
6 Nasaf 22 33 21 +12 34
7 Dinamo Samarqand 22 33 34 -1 30
8 Buxoro 22 32 29 +3 34
9 Olmaliq 22 31 29 +2 35
10 Andijan 22 27 28 -1 30
11 Qizilqum 22 23 30 -7 29
12 Bunyodkor 22 22 36 -14 22
13 Surkhon 22 19 28 -9 26
14 Kokand-1912 22 19 30 -11 20
15 Xorazm 22 18 32 -14 21
16 Mash'al 22 11 44 -33 4