Lokomotyvas Radviliškis vs Šilutė: result 0-1 and analysis
1 LygaRegular Season - 1Kick-off on April 12, 2014 at 02:30 PM (UTC)Panevėžio futbolo akademijos stadionas, Panevėžys
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What was the result of Lokomotyvas Radviliškis vs Šilutė?
Šilutė won 0-1 on April 12, 2014.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Lokomotyvas Radviliškis have 7 wins, 2 draws and 6 defeats; Šilutė have 3, 3 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2013 | Palanga(home) | 6-0 | 1 Lyga |
| Oct 19, 2013 | Žalgirietis(home) | 0-6 | 1 Lyga |
| Oct 12, 2013 | Šilutė(away) | 1-1 | 1 Lyga |
| Oct 6, 2013 | Baltija(home) | 6-2 | 1 Lyga |
| Sep 29, 2013 | Polonija(away) | 5-1 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2013 | Baltija(home) | 1-3 | 1 Lyga |
| Oct 19, 2013 | Polonija(away) | 1-2 | 1 Lyga |
| Oct 12, 2013 | Lokomotyvas Radviliškis(home) | 1-1 | 1 Lyga |
| Oct 5, 2013 | Žalgirietis(away) | 1-1 | 1 Lyga |
| Sep 28, 2013 | Palanga(home) | 4-2 | 1 Lyga |
What does the head-to-head say?
Across the last 3 meetings: 1 Lokomotyvas Radviliškis win(s), 2 draw(s), 0 Šilutė win(s).
| Date | Score | Competition |
|---|---|---|
| Oct 12, 2013 | Šilutė 1-1 Lokomotyvas Radviliškis | 1 Lyga |
| Jun 29, 2013 | Šilutė 0-3 Lokomotyvas Radviliškis | 1 Lyga |
| Apr 14, 2013 | Lokomotyvas Radviliškis 0-0 Šilutė | 1 Lyga |
Last archived meeting: Šilutė vs Lokomotyvas Radviliškis on Oct 12, 2013
How many goals should we expect?
Lokomotyvas Radviliškis score 2.3 and concede 2.3 goals per match over their last 15; Šilutė score 0.8 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Lokomotyvas Radviliškis | 2.3 | 2.3 | 3 | 9/15 | 12/15 |
| Šilutė | 0.8 | 1.6 | 2 | 6/15 | 5/15 |
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