Statistics / Football / Lithuania. A Lyga / Šiauliai vs Hegelmann Litauen

Šiauliai vs Hegelmann Litauen Statistics & Analysis

Šiauliai Šiauliai
Sep 13, 2026 - 14:00
0 1.26
0 1.34
xG Accuracy: 49%
Hegelmann Litauen Hegelmann Litauen
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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 Under 2.5 (0 goals) ✔ Correct
  • Both Teams To Score BTTS No No ✔ Correct
  • 1X2 Hegelmann Litauen Draw ✖ Incorrect
  • Correct Score Insights 1-1, 0-1, 1-0, 1-2, 2-1 0-0 ✖ Incorrect

Validation Report

Immutable Snapshot

Prediction Time: Sep 07, 2026 · 01:43 UTC Snapshot ID: dp-7441847

Closing Odds 2.66
AI Fair Odds —
CLV +0.0%
Final Result Draw · Šiauliai 0–0 Hegelmann Litauen
Prediction ✖ Missed
Decision Grade C

Model Performance

This prediction contributes to:

  • Primary Bets ROI (180d): -100.0%

Market intelligence

Supporting read on how the prioritized closing feed moved versus the model — use after the Primary pick above.

Market briefing

Market remained largely stable before kickoff. No meaningful late implied-price shift was detected between PRE30 and PRE5 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Draw (1X2), Under 2.5 goals meaningfully above what those closing snapshots implied — that gap is a static “model vs. price” read, not a late steam or chase story.

The model still exceeds closing implied on Under 2.5 goals by about 4.8 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market Model % Closing impl. % Gap (pp)
Šiauliai (1X2) 33.4 34.9 -1.5
Draw (1X2) 29.6 28.2 +1.4
Hegelmann Litauen (1X2) 37.0 37.0 +0.1
Over 2.5 goals 48.2 53.0 -4.8
Under 2.5 goals 51.8 47.0 +4.8
What this means

In plain terms: the model lands near 51.8% on Under 2.5 goals, while the closing snapshot implied about 47.0%. The difference — about 4.8 percentage points — is the largest model-vs.-market gap highlighted on this page.

Quick definitions: “closing implied” is the probability for that outcome implied by the final captured odds (after a simple de-vig). “Gap (pp)” is the model percentage minus that implied value, in percentage points (pp).

Closing-window line move

Single prioritized bookmaker per snapshot (not all books). Capture path: PRE30 → PRE5 · Book: Pinnacle

Column tags in parentheses: Closing uses the first available snapshot in PRE1→PRE5→PRE10→PRE30; Early uses the first available in PRE30→PRE10→PRE5 that is not the same capture as Closing.

Detailed capture odds are folded below — movement was negligible on de-vig implied prices.

View full line-by-line capture table
Market Early (PRE30) Closing (PRE5) Implied Δ (pp)
Šiauliai (1X2) 2.66 2.66 0.0
Draw (1X2) 3.29 3.29 0.0
Hegelmann Litauen (1X2) 2.51 2.51 0.0
Over 2.5 goals 1.78 1.78 0.0
Under 2.5 goals 2.01 2.01 0.0

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: A Lyga
  • Fixture: Šiauliai vs Hegelmann Litauen
  • Kickoff: 2026-09-13 14:00:00
  • 1X2 (model): Home 33.4% · Draw 29.6% · Away 37.0%
  • xG (showing): Šiauliai 1.26 — Hegelmann Litauen 1.34 (total xG ≈ 2.6)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 51.8% · Implied: 46.4% · Probability edge: +5.4 pts · Est. EV: +8.3%
  • BTTS (model): Yes 54.5% · No 45.5%
  • 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: Primary Bet

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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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