Дайнава vs ТрансИНВЕСТ Вильнюс Statistics & Analysis

Дайнава

Jun 24, 2026 - 16:00

1(2) 1.03

1(1) 1.57

xG Accuracy: 85%

ТрансИНВЕСТ Вильнюс

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Отслеживаемые рынки против результата матча

Каждая строка сравнивает предматчевый уклон модели с результатом матча.

Рынок Прогноз Результат Исход
Тотал больше / меньше 2.5 Тотал меньше 2.5 Тотал меньше 2.5 (2 голы) ✔ Верно
Обе забьют Обе забьют (BTTS) Нет Да ✖ Неверно
1X2 ТрансИНВЕСТ Вильнюс Ничья ✖ Неверно
Инсайты по точному счету 1-1, 0-1, 1-2, 0-2, 1-0 1-1 ✔ Верно

Validation Report

Immutable Snapshot

Prediction Time: Jul 24, 2026 · 21:42 UTC Snapshot ID: dp-1646610

Closing Odds Pending

AI Fair Odds —

CLV Pending

Final Result Draw · Дайнава 1–1 ТрансИНВЕСТ Вильнюс

Prediction ✖ Missed

Decision Grade F

Model Performance

This prediction contributes to:

Primary Bets ROI (180d): -100.0%

AI обзор матча

AI краткий обзор матча

Quick read on how the model reads this matchup.

League: Кубок Литвы
Fixture: Дайнава vs ТрансИНВЕСТ Вильнюс
Kickoff: 2026-06-24 16:00:00
1X2 (model): Home 23.3% · Draw 28.4% · Away 48.3%
xG (showing): Дайнава 1.03 — ТрансИНВЕСТ Вильнюс 1.57 (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): Value lean (pricing): O/U 2.5 Under 2.5; BTTS No
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.

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

Историческая рекомендация

Историческое решение: AI Value Alert - No Primary Bet

Исход: Missed — Pre-match 1X2 lean did not match the full-time result.

Факторы риска, учтенные до начала матча

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%).