Žalgiris II vs Auska: result 2-0 and analysis
1 LygaRegular Season - 33Kick-off on October 24, 2015 at 03:00 PM (UTC)Vilniaus LFF stadionas, Vilnius
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What was the result of Žalgiris II vs Auska?
Žalgiris II won 2-0 on October 24, 2015.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Žalgiris II have 12 wins, 2 draws and 1 defeat; Auska have 3, 2 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 21, 2015 | Lokomotyvas Radviliškis(home) | 4-1 | 1 Lyga |
| Oct 7, 2015 | Tauras(home) | 12-0 | 1 Lyga |
| Oct 3, 2015 | Džiugas Telšiai(away) | 2-1 | 1 Lyga |
| Sep 26, 2015 | Banga(home) | 1-0 | 1 Lyga |
| Sep 20, 2015 | Palanga(home) | 2-2 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 17, 2015 | Džiugas Telšiai(away) | 0-2 | 1 Lyga |
| Oct 4, 2015 | Kruoja II(home) | 0-3 | 1 Lyga |
| Sep 26, 2015 | Šilas(away) | 3-3 | 1 Lyga |
| Sep 19, 2015 | Minija(home) | 3-1 | 1 Lyga |
| Sep 13, 2015 | Banga(away) | 1-3 | 1 Lyga |
What does the head-to-head say?
In the last meeting: 1 Žalgiris II win, 0 draws, 0 Auska wins.
| Date | Score | Competition |
|---|---|---|
| Jun 28, 2015 | Auska 1-4 Žalgiris II | 1 Lyga |
How many goals should we expect?
Žalgiris II score 3.5 and concede 0.8 goals per match over their last 15; Auska score 1.1 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Žalgiris II | 3.5 | 0.8 | 7 | 8/15 | 13/15 |
| Auska | 1.1 | 2.3 | 0 | 8/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Žalgiris II | 26 | 14 | 4 | 8 | 40 | 33 | 46 |
A question about Žalgiris II vs Auska?
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