Lokomotyvas Radviliškis vs Kražantė: result 3-3 and analysis
1 LygaRegular Season - 11Kick-off on June 3, 2016 at 04:00 PM (UTC)Radviliškio miesto centrinis stadionas, Radviliškis
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What was the result of Lokomotyvas Radviliškis vs Kražantė?
Lokomotyvas Radviliškis and Kražantė drew 3-3 on June 3, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Lokomotyvas Radviliškis have 2 wins, 4 draws and 9 defeats; Kražantė have 5, 1 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 28, 2016 | Dainava(home) | 1-4 | 1 Lyga |
| May 14, 2016 | Hegelmann Litauen(home) | 2-2 | 1 Lyga |
| May 10, 2016 | Kaunas(away) | 0-2 | 1 Lyga |
| Apr 30, 2016 | Panevėžys(home) | 0-0 | 1 Lyga |
| Apr 22, 2016 | Vilniaus Vytis(away) | 0-5 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 28, 2016 | Kaunas(home) | 3-1 | 1 Lyga |
| May 22, 2016 | Palanga(away) | 1-1 | 1 Lyga |
| May 14, 2016 | Dainava(home) | 1-3 | 1 Lyga |
| May 8, 2016 | Džiugas Telšiai(home) | 2-3 | 1 Lyga |
| Apr 30, 2016 | Nevėžis(away) | 1-5 | 1 Lyga |
What does the head-to-head say?
Across the last 2 meetings: 1 Lokomotyvas Radviliškis win(s), 0 draw(s), 1 Kražantė win(s).
| Date | Score | Competition |
|---|---|---|
| Aug 29, 2015 | Kražantė 1-0 Lokomotyvas Radviliškis | 1 Lyga |
| May 16, 2015 | Lokomotyvas Radviliškis 3-0 Kražantė | 1 Lyga |
Last archived meeting: Kražantė vs Lokomotyvas Radviliškis on Aug 29, 2015
How many goals should we expect?
Lokomotyvas Radviliškis score 1.1 and concede 2.7 goals per match over their last 15; Kražantė score 1.6 and concede 2.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Lokomotyvas Radviliškis | 1.1 | 2.7 | 2 | 10/15 | 11/15 |
| Kražantė | 1.6 | 2.7 | 3 | 8/15 | 11/15 |
Over the last 15 matches in all competitions.
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