Bukovyna vs Kalush: result 1-2 and analysis
Druha LigaGroup A - 18Kick-off on October 27, 2019 at 12:00 PM (UTC)Stadion Bukovyna, Chernivtsi
Full time
What was the result of Bukovyna vs Kalush?
Kalush won 1-2 on October 27, 2019.
Goalscorers
- 53′Gabriel SantosKalush
- 83′B. IvanchenkoBukovyna
- 90′Volodymyr SavoshkoKalush
What is the recent form of both teams?
Over their last 15 matches in all competitions, Bukovyna have 5 wins, 2 draws and 8 defeats; Kalush have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2019 | Polessya(away) | 2-2 | Druha Liga |
| Oct 13, 2019 | Dinaz Vyshhorod(home) | 0-1 | Druha Liga |
| Oct 9, 2019 | Nyva Ternopil(away) | 1-2 | Druha Liga |
| Oct 5, 2019 | Obolon'-Brovar II(home) | 3-0 | Druha Liga |
| Sep 30, 2019 | Uzhhorod(away) | 0-1 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2019 | Dinaz Vyshhorod(home) | 1-1 | Druha Liga |
| Oct 19, 2019 | Nyva Ternopil(away) | 3-0 | Druha Liga |
| Oct 13, 2019 | Obolon'-Brovar II(home) | 1-1 | Druha Liga |
| Oct 9, 2019 | Uzhhorod(away) | 0-1 | Druha Liga |
| Oct 5, 2019 | Nyva Vinnytsya(home) | 2-0 | Druha Liga |
What does the head-to-head say?
Across the last 5 meetings: 2 Bukovyna win(s), 1 draw(s), 2 Kalush win(s).
| Date | Score | Competition |
|---|---|---|
| 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 1.5 and concede 1.7 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 | 1.5 | 1.7 | 2 | 8/15 | 9/15 |
| Kalush | 1.3 | 1.1 | 5 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
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