Jonava vs Suduva Marijampole: result 1-1 and analysis
A LygaRegular Season - 1Kick-off on March 6, 2016 at 11:00 AM (UTC)Nacionalinės futbolo akademijos stadionas, Kaunas
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What was the result of Jonava vs Suduva Marijampole?
Jonava and Suduva Marijampole drew 1-1 on March 6, 2016.
Goalscorers
- 23′A. ŠušnjarJonava
- 84′Tomas RadzineviciusSuduva Marijampole
What is the recent form of both teams?
Over their last 15 matches in all competitions, Jonava have 12 wins, 1 draw and 2 defeats; Suduva Marijampole have 11, 0 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 31, 2015 | Džiugas Telšiai(home) | 2-0 | 1 Lyga |
| Oct 25, 2015 | Kruoja II(away) | 3-0 | 1 Lyga |
| Oct 17, 2015 | Tauras(away) | 11-0 | 1 Lyga |
| Oct 11, 2015 | FK Panevezys(home) | 3-1 | 1 Lyga |
| Oct 3, 2015 | Palanga(away) | 3-0 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 28, 2015 | Atlantas(away) | 1-2 | A Lyga |
| Nov 22, 2015 | FK Zalgiris Vilnius(home) | 1-3 | A Lyga |
| Nov 10, 2015 | Kauno Žalgiris(home) | 5-1 | A Lyga |
| Oct 31, 2015 | Šiauliai(home) | 5-0 | A Lyga |
| Oct 25, 2015 | Granitas Klaipėda(away) | 8-1 | A Lyga |
How many goals should we expect?
Jonava score 3.1 and concede 0.6 goals per match over their last 15; Suduva Marijampole score 2.5 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Jonava | 3.1 | 0.6 | 8 | 6/15 | 10/15 |
| Suduva Marijampole | 2.5 | 0.9 | 8 | 5/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Suduva Marijampole | 29 | 13 | 11 | 5 | 39 | 29 | 50 |
A question about Jonava vs Suduva Marijampole?
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