Statistics / Football / Lithuania. A Lyga / Panevėžys vs Šiauliai

Panevėžys vs Šiauliai Statistics & Analysis

Panevėžys Panevėžys
Jun 20, 2026 - 11:15
3 1.38
2 1.22
xG Accuracy: 52%
Šiauliai Šiauliai
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Tracked markets vs full-time result

Each row compares the pre-match model lean to the full-time result.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 Panevėžys Panevėžys ✔ Correct
  • Correct Score Insights 1-1, 1-0, 0-1, 2-1, 1-2 3-2 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Aug 19, 2026 · 11:50 UTC Snapshot ID: dp-4589213

Closing Odds Pending
AI Fair Odds —
CLV Pending
Final Result Panevėžys win · Panevėžys 3–2 Šiauliai
Prediction ✔ Correct
Decision Grade B-

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

AI match briefing

AI Match Summary

Below is a compact, numbers-first snapshot aligned with the same engine as the cards above.

  • League: A Lyga
  • Fixture: Panevėžys vs Šiauliai
  • Kickoff: 2026-06-20 11:15:00
  • 1X2 (model): Home 39.0% · Draw 29.5% · Away 31.5%
  • xG (showing): Panevėžys 1.38 — Šiauliai 1.22 (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): Value lean (pricing): O/U 2.5 Under 2.5; BTTS Yes
  • BTTS (model): Yes N/A · No N/A
  • Correct score (top bin): N/A

The decision block shows no default Primary: Primary needs consensus EV ≥ +5.0% plus strength/reliability/calibration gates. A separate Lean/tracked gate is +2.0% (selective only). Lean labels are directional only — not bankroll-sized recommendations.

Prefer skipping to over-staking when the engine is honest about missing edge.

Historical Recommendation

Historical Decision: No Primary Bet

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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Back to Statistics
A Lyga A Lyga — Standings
# TEAM MP W D L PTS
1 Kauno Žalgiris 28 14 9 5 51
2 Suduva Marijampole 28 13 11 4 50
3 TransINVEST Vilnius 28 13 6 9 45
4 FK Zalgiris Vilnius 28 13 5 10 44
5 Banga 28 11 8 9 41
6 Džiugas Telšiai 28 10 8 10 38
7 Panevėžys 28 9 5 14 32
8 Hegelmann Litauen 29 4 14 11 26
9 Šiauliai 29 3 8 18 17
10 FK Trakai 0 0 0 0 0
# TEAM MP GS GC +/- PTS
1 Kauno Žalgiris 28 56 20 +36 51
2 TransINVEST Vilnius 28 43 35 +8 45
3 FK Zalgiris Vilnius 28 41 34 +7 44
4 Suduva Marijampole 28 39 25 +14 50
5 Džiugas Telšiai 28 36 40 -4 38
6 Banga 28 32 28 +4 41
7 Hegelmann Litauen 29 31 48 -17 26
8 Panevėžys 28 29 43 -14 32
9 Šiauliai 29 24 58 -34 17
10 FK Trakai 0 0 0 0 0