Predictions / Football / Uzbekistan. Cup / Bunyodkor vs Lokomotiv

Prediction Audit: Bunyodkor vs Lokomotiv Prediction, Odds & AI Betting Tips

Bunyodkor Bunyodkor
Sep 15, 2026 - 13:30
0 1.29
1 1.31
xG Accuracy: 64%
Lokomotiv Lokomotiv

AI correctly predicted the Lokomotiv win.

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

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 Lokomotiv Lokomotiv ✔ Correct
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-1 ✔ Correct

Model vs Closing Market

Strong Disagreement

The closing market prices Lokomotiv higher than the statistical model.

Largest probability gap: Lokomotiv -21.5 pp

Outcome Model Closing Market Difference Signal
Bunyodkor 34.7% 19.5% +15.2 pp Model Edge
Draw 29.6% 23.3% +6.3 pp Model Higher
Lokomotiv 35.6% 57.2% -21.5 pp Market Higher

The closing market estimates Lokomotiv's win probability at 57.2%, compared with the model's estimate of 35.6%, a difference of 21.5 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 (Lokomotiv win 0–1).

Post Match Insights

What worked

  • Exact score 0–1 fell within the model's highlighted bins

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

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Lokomotiv higher (57.1% vs model 35.6%, 21.5 pp), but the model's lean was validated (Lokomotiv win 0–1).

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Prediction Timeline

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

  1. Sep 15, 2026 · 13:29 UTC Forecast generated
    • Model 1X2 · Bunyodkor 34.7% · Draw 29.7% · Lokomotiv 35.6%
    • xG · Bunyodkor 1.29 — Lokomotiv 1.31
  2. Sep 15, 2026 · 12:59 UTC Opening odds snapshot PRE30
    • 1X2 odds · Bunyodkor 4.60 · Draw 3.85 · Lokomotiv 1.57
    • Implied 1X2 · Bunyodkor 19.5% · Draw 23.3% · Lokomotiv 57.2%
    • Bookmaker · Pinnacle
  3. Sep 15, 2026 · 13:29 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Bunyodkor 4.60 · Draw 3.85 · Lokomotiv 1.57
    • Implied 1X2 · Bunyodkor 19.5% · Draw 23.3% · Lokomotiv 57.2%
    • Bookmaker · Pinnacle
  4. Sep 15, 2026 · 13:30 UTC Kickoff
  5. FT Full-time result Lokomotiv win · 0–1
  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: Cautious / Wait

Historical label: Originally displayed as "Wait for validation".

Historical Decision Wait
Outcome Validated
Pre-match metrics (historical context)
Prediction Reliability 52/100 · Moderate
  • Validation: Warning
  • Large market gap (22 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Pricing remains divergent
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 33/100

Validation Report

Immutable Snapshot

Prediction Time: Sep 09, 2026 · 02:20 UTC Snapshot ID: dp-7702121

Closing Odds 1.57
AI Fair Odds —
CLV Pending
Final Result Lokomotiv win · Bunyodkor 0–1 Lokomotiv
Prediction ✔ Correct
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: Cup
  • Fixture: Bunyodkor vs Lokomotiv
  • Kickoff: 2026-09-15 13:30:00
  • 1X2 (model): Home 34.7% · Draw 29.7% · Away 35.6%
  • xG (showing): Bunyodkor 1.29 — Lokomotiv 1.31 (total xG ≈ 2.6)
  • Value headline: At least one tracked line reaches the headline EV threshold — align with the hero / Primary card if shown.
  • Structural leans (not bets): Structural lean (model): O/U 2.5 Under 2.5 (Under 2.5 51.8% · Over 2.5 48.2%); BTTS Yes (Yes 54.5% · No 45.5%) Value lean (pricing): O/U 2.5 Over 2.5; BTTS Yes
  • BTTS (model): Yes 54.5% · No 45.5%
  • Correct score (top bin): 1-1 (12.6%)

Saying “no value” on a snapshot is a feature, not a bug: it protects readers from forcing a play when the edge is not there.

If lines move materially, re-run generation or refresh — implied probabilities and any future EV readouts will change first.

Historical Recommendation

Historical Decision: Wait

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 30, 2026 (UTC)

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