Panevėžys vs Suduva Marijampole: result 1-2 and analysis
A LygaRegular Season - 7Kick-off on April 19, 2019 at 02:30 PM (UTC)Žemynos progimnazijos stadionas, Panevėžys
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What was the result of Panevėžys vs Suduva Marijampole?
Suduva Marijampole won 1-2 on April 19, 2019.
Goalscorers
- 33′E. JankauskasSuduva Marijampole
- 40′V. GašpuitisPanevėžys
- 74′S. GotalSuduva Marijampole
What is the recent form of both teams?
Over their last 15 matches in all competitions, Panevėžys have 6 wins, 3 draws and 6 defeats; Suduva Marijampole have 11, 1 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2019 | Atlantas(away) | 1-2 | A Lyga |
| Apr 7, 2019 | FK Trakai(home) | 1-2 | A Lyga |
| Mar 30, 2019 | Kauno Žalgiris(away) | 0-2 | A Lyga |
| Mar 17, 2019 | Palanga(away) | 1-1 | A Lyga |
| Mar 9, 2019 | FK Zalgiris Vilnius(home) | 0-3 | A Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2019 | Palanga(home) | 3-0 | A Lyga |
| Apr 7, 2019 | FK Zalgiris Vilnius(away) | 0-1 | A Lyga |
| Mar 31, 2019 | Stumbras(away) | 0-2 | A Lyga |
| Mar 16, 2019 | Kauno Žalgiris(home) | 1-0 | A Lyga |
| Mar 10, 2019 | Atlantas(away) | 5-0 | A Lyga |
How many goals should we expect?
Panevėžys score 2.1 and concede 1.3 goals per match over their last 15; Suduva Marijampole score 2.3 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Panevėžys | 2.1 | 1.3 | 3 | 9/15 | 9/15 |
| Suduva Marijampole | 2.3 | 0.8 | 6 | 7/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Panevėžys sit 8th in A Lyga (23 points from 24 matches) and Suduva Marijampole sit 1st (42 points from 23 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Suduva Marijampole | 23 | 11 | 9 | 3 | 33 | 17 | 42 |
| 8 | Panevėžys | 24 | 6 | 5 | 13 | 21 | 41 | 23 |
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy