Luunja vs Tallinna Kalev: prediction and stats
Esiliiga ARegular Season - 8Kick-off on June 19, 2021 at 10:00 AM (UTC)Tartu Sepa tänava staadion, Tartu
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Luunja have 2 wins, 3 draws and 10 defeats; Tallinna Kalev have 8, 3 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 12, 2021 | Maardu(away) | 2-2 | Esiliiga A |
| May 31, 2021 | FCI Levadia II(home) | 3-4 | Esiliiga A |
| May 27, 2021 | Elva(home) | 1-0 | Esiliiga A |
| May 16, 2021 | Nõmme United(home) | 1-6 | Esiliiga A |
| May 9, 2021 | Pärnu(away) | 0-2 | Esiliiga A |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 30, 2021 | Elva(away) | 4-0 | Esiliiga A |
| May 27, 2021 | Tartu Welco(home) | 2-1 | Esiliiga A |
| May 21, 2021 | FCI Levadia II(away) | 4-3 | Esiliiga A |
| May 15, 2021 | Paide II(home) | 0-2 | Esiliiga A |
| May 9, 2021 | Maardu(home) | 2-2 | Esiliiga A |
What does the head-to-head say?
Across the last 1 meetings: 0 Luunja win(s), 0 draw(s), 1 Tallinna Kalev win(s).
| Date | Score | Competition |
|---|---|---|
| May 6, 2021 | Luunja 1-5 Tallinna Kalev | Esiliiga A |
Last archived meeting: Luunja vs Tallinna Kalev on May 6, 2021
How many goals should we expect?
Luunja score 1.1 and concede 3.1 goals per match over their last 15; Tallinna Kalev score 2.1 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Luunja | 1.1 | 3.1 | 2 | 9/15 | 11/15 |
| Tallinna Kalev | 2.1 | 1.2 | 4 | 8/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 5 | Tallinna Kalev | 16 | 5 | 3 | 8 | 27 | 32 | 18 |
| 5 | Tallinna Kalev | 24 | 10 | 5 | 9 | 47 | 42 | 35 |
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