FK Trakai vs FK Zalgiris Vilnius: result 1-1 and analysis
A LygaRegular Season - 3Kick-off on March 21, 2014 at 05:00 PM (UTC)Vilniaus LFF stadionas, Vilnius
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What was the result of FK Trakai vs FK Zalgiris Vilnius?
FK Trakai and FK Zalgiris Vilnius drew 1-1 on March 21, 2014.
Goalscorers
- 8′Jakub WilkFK Zalgiris Vilnius
- 67′T. LabukasFK Trakai
What is the recent form of both teams?
Over their last 15 matches in all competitions, FK Trakai have 9 wins, 4 draws and 2 defeats; FK Zalgiris Vilnius have 8, 5 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 15, 2014 | Banga(away) | 0-1 | A Lyga |
| Mar 10, 2014 | Granitas Klaipėda(home) | 2-0 | A Lyga |
| Oct 27, 2013 | Šilas(home) | 2-0 | 1 Lyga |
| Oct 20, 2013 | Kauno Žalgiris(away) | 8-2 | 1 Lyga |
| Oct 12, 2013 | Granitas Klaipėda(home) | 5-1 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 16, 2014 | Suduva Marijampole(home) | 8-1 | A Lyga |
| Mar 9, 2014 | Šiauliai(home) | 3-1 | A Lyga |
| Nov 9, 2013 | Suduva Marijampole(home) | 1-3 | A Lyga |
| Nov 2, 2013 | Banga(away) | 1-1 | A Lyga |
| Oct 29, 2013 | Kruoja(away) | 0-0 | A Lyga |
How many goals should we expect?
FK Trakai score 2.3 and concede 0.9 goals per match over their last 15; FK Zalgiris Vilnius score 2.2 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| FK Trakai | 2.3 | 0.9 | 7 | 7/15 | 7/15 |
| FK Zalgiris Vilnius | 2.2 | 0.9 | 7 | 8/15 | 8/15 |
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 | FK Zalgiris Vilnius | 30 | 15 | 5 | 10 | 49 | 35 | 50 |
A question about FK Trakai vs FK Zalgiris Vilnius?
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