Bukovyna vs Kalush: prediction and stats
Druha LigaGroup A - 19Kick-off on April 25, 2021 at 12:00 AM (UTC)Stadion Bukovyna, Chernivtsi
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Bukovyna have 5 wins, 4 draws and 6 defeats; Kalush have 6, 3 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 19, 2021 | Podillya Khmelnytskyi(away) | 1-3 | Druha Liga |
| Apr 14, 2021 | Nyva Vinnytsya(home) | 1-0 | Druha Liga |
| Apr 9, 2021 | Uzhhorod(away) | 2-3 | Druha Liga |
| Apr 3, 2021 | Chayka(home) | 0-0 | Druha Liga |
| Mar 27, 2021 | Dinaz Vyshhorod(home) | 1-2 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 23, 2019 | Veres Rivne(home) | 2-1 | Druha Liga |
| Nov 16, 2019 | Podillya Khmelnytskyi(away) | 0-1 | Druha Liga |
| Nov 3, 2019 | Polessya(home) | 0-2 | Druha Liga |
| Oct 27, 2019 | Bukovyna(away) | 2-1 | Druha Liga |
| Oct 23, 2019 | Dinaz Vyshhorod(home) | 1-1 | Druha Liga |
What does the head-to-head say?
Across the last 6 meetings: 2 Bukovyna wins, 1 draw, 3 Kalush wins.
| Date | Score | Competition |
|---|---|---|
| Oct 27, 2019 | Bukovyna 1-2 Kalush | Druha Liga |
| Sep 4, 2019 | Kalush 0-2 Bukovyna | Druha Liga |
| May 25, 2019 | Kalush 1-3 Bukovyna | Druha Liga |
| Nov 11, 2018 | Kalush 2-0 Bukovyna | Druha Liga |
| Sep 9, 2018 | Bukovyna 0-3 Kalush | Druha Liga |
| Jul 18, 2018 | Kalush 2-2 Bukovyna | Cup |
How many goals should we expect?
Bukovyna score 1.3 and concede 1.3 goals per match over their last 15; Kalush score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Bukovyna | 1.3 | 1.3 | 5 | 8/15 | 9/15 |
| Kalush | 1.3 | 1.1 | 3 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
A question about Bukovyna vs Kalush?
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