Dainava vs Kražantė: result 0-0 and analysis
1 LygaRegular Season - 23Kick-off on September 3, 2016 at 03:00 PM (UTC)Alytaus m. centrinis stadionas, Marijampolė
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What was the result of Dainava vs Kražantė?
Dainava and Kražantė drew 0-0 on September 3, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Dainava have 8 wins, 2 draws and 5 defeats; Kražantė have 5, 2 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2016 | Šilutė(away) | 2-0 | 1 Lyga |
| Aug 20, 2016 | Palanga(home) | 2-2 | 1 Lyga |
| Aug 13, 2016 | Kaunas(away) | 5-0 | 1 Lyga |
| Aug 9, 2016 | Trakai II(away) | 2-1 | 1 Lyga |
| Aug 5, 2016 | Vilniaus Vytis(away) | 0-3 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 28, 2016 | Džiugas Telšiai(away) | 1-2 | 1 Lyga |
| Aug 24, 2016 | Šilas(away) | 1-5 | 1 Lyga |
| Aug 14, 2016 | Minija(home) | 4-0 | 1 Lyga |
| Aug 9, 2016 | Panevėžys(away) | 3-2 | 1 Lyga |
| Aug 5, 2016 | Hegelmann Litauen(home) | 1-5 | 1 Lyga |
What does the head-to-head say?
In the last meeting: 1 Dainava win, 0 draws, 0 Kražantė wins.
| Date | Score | Competition |
|---|---|---|
| May 14, 2016 | Kražantė 1-3 Dainava | 1 Lyga |
How many goals should we expect?
Dainava score 1.7 and concede 1.3 goals per match over their last 15; Kražantė score 2.0 and concede 2.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Dainava | 1.7 | 1.3 | 4 | 8/15 | 11/15 |
| Kražantė | 2.0 | 2.7 | 1 | 12/15 | 13/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Dainava | 26 | 11 | 8 | 7 | 37 | 27 | 41 |
A question about Dainava vs Kražantė?
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