Noah Jūrmala vs Rīgas FS: prediction and stats
VirsligaRegular Season - 27Kick-off on August 27, 2021 at 02:00 PM (UTC)
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Noah Jūrmala have 1 win, 1 draw and 13 defeats; Rīgas FS have 11, 1 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 18, 2021 | Valmiera / BSS(away) | 0-3 | Virsliga |
| Jul 13, 2021 | Metta / LU(away) | 0-7 | Virsliga |
| Jul 9, 2021 | BFC Daugavpils(home) | 1-4 | Virsliga |
| Jun 25, 2021 | Riga(away) | 1-2 | Virsliga |
| Jun 21, 2021 | Rīgas FS(away) | 0-5 | Virsliga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 21, 2021 | Auda(home) | 4-0 | Cup |
| Aug 12, 2021 | Gent(home) | 0-1 | UEFA Europa Conference League |
| Aug 9, 2021 | Skanste(away) | 2-0 | Cup |
| Aug 5, 2021 | Gent(away) | 2-2 | UEFA Europa Conference League |
| Aug 1, 2021 | Metta / LU(home) | 4-1 | Virsliga |
What does the head-to-head say?
Across the last 2 meetings: 0 Noah Jūrmala wins, 0 draws, 2 Rīgas FS wins.
| Date | Score | Competition |
|---|---|---|
| Jun 21, 2021 | Rīgas FS 5-0 Noah Jūrmala | Virsliga |
| Apr 29, 2021 | Rīgas FS 4-2 Noah Jūrmala | Virsliga |
Last archived meeting: Rīgas FS vs Noah Jūrmala on Jun 21, 2021
How many goals should we expect?
Noah Jūrmala score 0.7 and concede 3.7 goals per match over their last 15; Rīgas FS score 2.6 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Noah Jūrmala | 0.7 | 3.7 | 0 | 6/15 | 13/15 |
| Rīgas FS | 2.6 | 0.9 | 6 | 8/15 | 12/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Rīgas FS | 32 | 25 | 5 | 2 | 79 | 24 | 80 |
A question about Noah Jūrmala vs Rīgas FS?
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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