Sveikata vs Babrungas: result 1-3 and analysis
Cup1st RoundKick-off on May 22, 2021 at 11:00 AM (UTC)
Full time
What was the result of Sveikata vs Babrungas?
Babrungas won 1-3 on May 22, 2021.
Goalscorers
- 19′315274Sveikata
- 27′K. PaplauskasBabrungas
- 28′Edvinas MickevičiusBabrungas
- 64′D. KontenisBabrungas
Official lineup for Sveikata vs Babrungas
The starting elevens fielded at kick-off.
Sveikata
- AArtūras Pečiulis
- KKęstutis Balčiūnas
- MM. Kereiša
- II. Siaurusaitis
- TT. Krakauskas
- SS. Rekašius
- EE. Simanavičius
- DD. Ryckis
- MM. Kiškėnas
- RR. Gudelis
- JJustinas Popiera
Babrungas
- HHenrique Devens
- TT. Budrys
- VVytautas Birškys
- VVinicius Hess
- EEdvinas Mickevičius
- LLaurynas Gaudėšius
- VV. Butkus
- KK. Paplauskas
- SSalomao Kabula Muchalo Kimuamua
- DD. Kontenis
- MMaycon Douglas
What is the recent form of both teams?
Over their last 2 matches in all competitions, Sveikata have 1 win, 0 draws and 1 defeat; Babrungas have 6, 1 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 14, 2020 | Kauno Žalgiris(home) | 0-4 | Cup |
| Jun 30, 2020 | Utenis Utena(away) | 2-0 | Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 15, 2021 | Žalgiris II(home) | 2-3 | 1 Lyga |
| May 9, 2021 | Banga II(home) | 3-0 | 1 Lyga |
| Apr 24, 2021 | Minija(away) | 3-1 | 1 Lyga |
| Apr 17, 2021 | Neptūną Klaipėda(home) | 5-1 | 1 Lyga |
| Apr 9, 2021 | Kauno Žalgiris II(away) | 2-0 | 1 Lyga |
How many goals should we expect?
Sveikata score 1.0 and concede 2.0 goals per match over their last 2; Babrungas score 2.3 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sveikata | 1.0 | 2.0 | 1 | 0/2 | 1/2 |
| Babrungas | 2.3 | 1.5 | 3 | 7/10 | 8/10 |
Over the last 2 matches in all competitions.
A question about Sveikata vs Babrungas?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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