Garliava vs Dainava: result 1-2 and analysis
1 LygaRegular Season - 2Kick-off on March 26, 2022 at 12:00 PM (UTC)Garliavos Adomo Mitkaus mokyklos stadionas, Garliava
Full time
What was the result of Garliava vs Dainava?
Dainava won 1-2 on March 26, 2022.
Goalscorers
- 41′Y. HanadaDainava
- 64′?Dainava
- 76′?Garliava
What is the recent form of both teams?
Over their last 4 matches in all competitions, Garliava have 1 win, 1 draw and 2 defeats; Dainava have 3, 6 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 19, 2022 | Šiauliai II(home) | 0-2 | 1 Lyga |
| Sep 14, 2021 | Hegelmann Litauen(home) | 0-2 | Cup |
| Jun 16, 2021 | Šilutė(home) | 2-1 | Cup |
| May 22, 2021 | Viltis Vilnius(away) | 0-0 | Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 20, 2022 | Be1 NFA(away) | 1-1 | 1 Lyga |
| Nov 28, 2021 | Suduva Marijampole(away) | 1-0 | A Lyga |
| Nov 19, 2021 | Banga(away) | 1-1 | A Lyga |
| Nov 7, 2021 | FK Zalgiris Vilnius(home) | 0-2 | A Lyga |
| Oct 31, 2021 | Kauno Žalgiris(away) | 0-2 | A Lyga |
How many goals should we expect?
Garliava score 0.5 and concede 1.3 goals per match over their last 4; Dainava score 1.1 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Garliava | 0.5 | 1.3 | 1 | 1/4 | 1/4 |
| Dainava | 1.1 | 1.4 | 2 | 10/15 | 5/15 |
Over the last 4 matches in all competitions.
Where do both teams sit in the table?
Garliava sit 11th in 1 Lyga (29 points from 27 matches) and Dainava sit 6th (44 points from 27 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Dainava | 27 | 12 | 8 | 7 | 40 | 28 | 44 |
| 11 | Garliava | 27 | 8 | 5 | 14 | 32 | 33 | 29 |
A question about Garliava vs Dainava?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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How does Footlab AI compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy