Dnipro-1 vs Kolos Kovalivka: result 3-1 and analysis
Persha LigaRegular Season - 29Kick-off on May 19, 2019 at 02:00 PM (UTC)Dnipro Arena, Dnipro
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What was the result of Dnipro-1 vs Kolos Kovalivka?
Dnipro-1 won 3-1 on May 19, 2019.
Goalscorers
- 11′O. IlyinKolos Kovalivka
- 29′S. LoginovDnipro-1
- 45′O. NazarenkoDnipro-1
- 74′Oleksii ChychykovDnipro-1
What is the recent form of both teams?
Over their last 15 matches in all competitions, Dnipro-1 have 10 wins, 3 draws and 2 defeats; Kolos Kovalivka have 7, 5 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 15, 2019 | Obolon'-Brovar(away) | 1-1 | Persha Liga |
| May 11, 2019 | Prykarpattia(away) | 0-4 | Persha Liga |
| May 5, 2019 | Inhulets(home) | 3-3 | Persha Liga |
| May 1, 2019 | Balkany Zorya(away) | 2-0 | Persha Liga |
| Apr 22, 2019 | Kramatorsk(home) | 1-0 | Persha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 11, 2019 | Sumy(home) | 4-0 | Persha Liga |
| May 6, 2019 | Volyn(away) | 1-2 | Persha Liga |
| May 1, 2019 | Ahrobiznes Volochysk(home) | 1-0 | Persha Liga |
| Apr 26, 2019 | Metalist 1925 Kharkiv(away) | 0-0 | Persha Liga |
| Apr 18, 2019 | Hirnyk-Sport(away) | 1-2 | Persha Liga |
What does the head-to-head say?
Across the last 1 meetings: 0 Dnipro-1 win(s), 1 draw(s), 0 Kolos Kovalivka win(s).
| Date | Score | Competition |
|---|---|---|
| Oct 20, 2018 | Kolos Kovalivka 1-1 Dnipro-1 | Persha Liga |
Last archived meeting: Kolos Kovalivka vs Dnipro-1 on Oct 20, 2018
How many goals should we expect?
Dnipro-1 score 2.4 and concede 0.8 goals per match over their last 15; Kolos Kovalivka score 1.6 and concede 0.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Dnipro-1 | 2.4 | 0.8 | 9 | 4/15 | 9/15 |
| Kolos Kovalivka | 1.6 | 0.6 | 8 | 6/15 | 6/15 |
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