Metta / LU vs Babīte: prediction and stats
VirsligaRegular Season - 13Kick-off on June 27, 2017 at 12:00 AM (UTC)Daugavas Stadionā, Riga
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Metta / LU have 4 wins, 3 draws and 8 defeats; Babīte have 2, 2 and 11.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 17, 2017 | Jelgava(away) | 0-2 | Virsliga |
| Jun 2, 2017 | Riga(home) | 0-0 | Virsliga |
| May 28, 2017 | Rīgas FS(away) | 2-3 | Virsliga |
| May 21, 2017 | Spartaks Jurmala(away) | 0-1 | Virsliga |
| May 13, 2017 | FK Ventspils(home) | 1-1 | Virsliga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 16, 2017 | Spartaks Jurmala(home) | 0-1 | Virsliga |
| Jun 2, 2017 | FK Ventspils(away) | 0-1 | Virsliga |
| May 26, 2017 | FK Liepaja(home) | 1-2 | Virsliga |
| May 20, 2017 | Rīgas FS(away) | 1-2 | Virsliga |
| May 12, 2017 | Jelgava(home) | 0-5 | Virsliga |
What does the head-to-head say?
In the last meeting: 1 Metta / LU win, 0 draws, 0 Babīte wins.
| Date | Score | Competition |
|---|---|---|
| Apr 29, 2017 | Babīte 1-2 Metta / LU | Virsliga |
How many goals should we expect?
Metta / LU score 1.2 and concede 1.8 goals per match over their last 15; Babīte score 1.1 and concede 2.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Metta / LU | 1.2 | 1.8 | 1 | 10/15 | 9/15 |
| Babīte | 1.1 | 2.2 | 1 | 8/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Metta / LU | 36 | 8 | 7 | 21 | 39 | 74 | 31 |
A question about Metta / LU vs Babīte?
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