Predictions / Football / Lithuania. Cup / Šiauliai vs Kauno Žalgiris

Prediction Audit: Šiauliai vs Kauno Žalgiris Prediction, Odds & AI Betting Tips

Šiauliai Šiauliai
Sep 03, 2026 - 14:15
0 1.24
1 1.36
xG Accuracy: 64%
Kauno Žalgiris Kauno Žalgiris

AI correctly predicted the Kauno Žalgiris win.

The match finished 0–1, 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 Kauno Žalgiris Kauno Žalgiris ✔ 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 Kauno Žalgiris higher than the statistical model.

Largest probability gap: Kauno Žalgiris -29.4 pp

Outcome Model Closing Market Difference Signal
Šiauliai 32.4% 12.6% +19.8 pp Model Edge
Draw 29.6% 20.0% +9.6 pp Model Higher
Kauno Žalgiris 38.0% 67.4% -29.4 pp Market Higher

The closing market estimates Kauno Žalgiris's win probability at 67.4%, compared with the model's estimate of 38.0%, a difference of 29.4 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 (Kauno Žalgiris win 0–1).

Post Match Insights

What worked

  • Under 2.5 goals aligned with the xG profile
  • 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

Market lesson

Large model–market gaps do not automatically mean the market is right. Here the closing market priced Kauno Žalgiris higher (67.4% vs model 38.0%, 29.4 pp), but the model's lean was validated (Kauno Žalgiris win 0–1).

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Prediction Timeline

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

  1. Sep 03, 2026 · 14:14 UTC Forecast generated
    • Model 1X2 · Šiauliai 32.4% · Draw 29.6% · Kauno Žalgiris 38.0%
    • xG · Šiauliai 1.24 — Kauno Žalgiris 1.36
  2. Sep 03, 2026 · 13:44 UTC Opening odds snapshot PRE30
    • 1X2 odds · Šiauliai 7.07 · Draw 4.44 · Kauno Žalgiris 1.32
    • Implied 1X2 · Šiauliai 12.6% · Draw 20.0% · Kauno Žalgiris 67.4%
    • Bookmaker · Pinnacle
  3. Sep 03, 2026 · 14:14 UTC Closing snapshot recorded PRE1
    • 1X2 odds · Šiauliai 7.07 · Draw 4.44 · Kauno Žalgiris 1.32
    • Implied 1X2 · Šiauliai 12.6% · Draw 20.0% · Kauno Žalgiris 67.4%
    • Bookmaker · Pinnacle
  4. Sep 03, 2026 · 14:15 UTC Kickoff
  5. FT Full-time result Kauno Žalgiris 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 48/100 · Moderate
  • Validation: Warning
  • Large market gap (29 pp)
Evidence ★★★★★
  • No strong statistical edge
  • Market strongly disagrees on price
  • Validation warning
Pricing proximity (inverse gap) 0/100
Betting Confidence 31/100

Validation Report

Immutable Snapshot

Prediction Time: Aug 26, 2026 · 02:07 UTC Snapshot ID: dp-5502385

Closing Odds 1.32
AI Fair Odds —
CLV Pending
Final Result Kauno Žalgiris win · Šiauliai 0–1 Kauno Žalgiris
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: Cup
  • Fixture: Šiauliai vs Kauno Žalgiris
  • Kickoff: 2026-09-03 14:15:00
  • 1X2 (model): Home 32.4% · Draw 29.6% · Away 38.0%
  • xG (showing): Šiauliai 1.24 — Kauno Žalgiris 1.36 (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 54.4% · No 45.6%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes 54.4% · No 45.6%
  • Correct score (top bin): 1-1 (12.5%)

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: 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 28, 2026 (UTC)

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