Hegelmann Litauen vs Džiugas Telšiai Statistics & Analysis

Hegelmann Litauen

Jun 17, 2026 - 15:30

1 1.41

1 1.19

xG Accuracy: 85%

Džiugas Telšiai

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

Validation Report

Immutable Snapshot

Prediction Time: Jul 25, 2026 · 04:44 UTC Snapshot ID: dp-1676975

Closing Odds 2.56

AI Fair Odds —

CLV +0.0%

Final Result Draw · Hegelmann Litauen 1–1 Džiugas Telšiai

Prediction ✖ Missed

Decision Grade F

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 PRE1 on the prioritized bookmaker snapshot.

Despite limited late movement, the model still prices Hegelmann Litauen (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 Hegelmann Litauen (1X2) by about 5.1 percentage points — the clearest mispricing signal summarized on this page.

Model vs. closing implied

Market	Model %	Closing impl. %	Gap (pp)
Hegelmann Litauen (1X2)	40.5	35.4	+5.1
Draw (1X2)	29.4	28.4	+1.0
Džiugas Telšiai (1X2)	30.1	36.2	-6.1
Over 2.5 goals	48.2	50.3	-2.1
Under 2.5 goals	51.8	49.7	+2.1

What this means

In plain terms: the model lands near 40.5% on Hegelmann Litauen (1X2), while the closing snapshot implied about 35.4%. The difference — about 5.1 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 → PRE1 · 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 (PRE1)
Hegelmann Litauen (1X2)	2.62	2.62
Draw (1X2)	3.26	3.26
Džiugas Telšiai (1X2)	2.56	2.56
Over 2.5 goals	1.89	1.89
Under 2.5 goals	1.91	1.91

AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

League: A Lyga
Fixture: Hegelmann Litauen vs Džiugas Telšiai
Kickoff: 2026-06-17 15:30:00
1X2 (model): Home 40.5% · Draw 29.4% · Away 30.1%
xG (showing): Hegelmann Litauen 1.41 — Džiugas Telšiai 1.19 (total xG ≈ 2.6)
Value headline: None — no positive EV on tracked lines at current best prices (same as the decision block: no default bet).
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 54.2% · No 45.8%) Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
BTTS (model): Yes 54.2% · No 45.8%
Correct score (top bin): 1-1 (12.5%)

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.

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

Historical Recommendation

Historical Decision: No 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

October 01, 2026 (UTC)

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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