Zirka vs Prykarpattia: prediction and stats
Persha LigaRegular Season - 23Kick-off on April 17, 2019 at 12:00 AM (UTC)Stadion Zirka, Kropyvnytskyi
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Zirka have 2 wins, 2 draws and 11 defeats; Prykarpattia have 4, 3 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 17, 2018 | Dnipro-1(away) | 0-4 | Persha Liga |
| Nov 10, 2018 | Sumy(home) | 3-3 | Persha Liga |
| Nov 3, 2018 | Volyn(away) | 1-3 | Persha Liga |
| Oct 27, 2018 | Ahrobiznes Volochysk(away) | 0-5 | Persha Liga |
| Oct 20, 2018 | Metalist 1925 Kharkiv(home) | 0-3 | Persha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 13, 2019 | Hirnyk-Sport(home) | 1-0 | Persha Liga |
| Apr 5, 2019 | Ruh Lviv(away) | 2-2 | Persha Liga |
| Mar 27, 2019 | Mykolaiv(home) | 1-2 | Persha Liga |
| Mar 23, 2019 | Kolos Kovalivka(away) | 1-3 | Persha Liga |
| Nov 17, 2018 | Kramatorsk(away) | 1-3 | Persha Liga |
What does the head-to-head say?
In the last meeting: 0 Zirka wins, 0 draws, 1 Prykarpattia win.
| Date | Score | Competition |
|---|---|---|
| Sep 9, 2018 | Prykarpattia 7-1 Zirka | Persha Liga |
How many goals should we expect?
Zirka score 0.9 and concede 2.9 goals per match over their last 15; Prykarpattia score 1.6 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Zirka | 0.9 | 2.9 | 1 | 7/15 | 11/15 |
| Prykarpattia | 1.6 | 1.5 | 3 | 9/15 | 9/15 |
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 | Prykarpattia | 14 | 4 | 4 | 6 | 13 | 18 | 16 |
A question about Zirka vs Prykarpattia?
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