Mykolaiv vs Ruh Lviv: result 4-1 and analysis
Persha LigaRegular Season - 8Kick-off on September 8, 2018 at 02:00 PM (UTC)Tsentralnyi miskyi Stadion, Mykolajiv
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What was the result of Mykolaiv vs Ruh Lviv?
Mykolaiv won 4-1 on September 8, 2018.
Goalscorers
- 18′Roman PopovMykolaiv
- 19′Mykhailo KozakRuh Lviv
- 37′D. SartinaMykolaiv
- 59′Ivan AntoniukMykolaiv
- 90′Tymofii BryzhchukMykolaiv
What is the recent form of both teams?
Over their last 15 matches in all competitions, Mykolaiv have 7 wins, 3 draws and 5 defeats; Ruh Lviv have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 1, 2018 | Kramatorsk(home) | 0-0 | Persha Liga |
| Aug 26, 2018 | Kolos Kovalivka(away) | 0-2 | Persha Liga |
| Aug 22, 2018 | Balkany Zorya(away) | 1-0 | Cup |
| Aug 17, 2018 | Prykarpattia(home) | 1-0 | Persha Liga |
| Aug 11, 2018 | Inhulets(away) | 0-2 | Persha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 1, 2018 | Kolos Kovalivka(home) | 0-2 | Persha Liga |
| Aug 26, 2018 | Prykarpattia(away) | 0-1 | Persha Liga |
| Aug 22, 2018 | Cherkashchyna-Akademiya(away) | 1-3 | Cup |
| Aug 18, 2018 | Inhulets(home) | 0-1 | Persha Liga |
| Aug 11, 2018 | Balkany Zorya(away) | 1-2 | Persha Liga |
What does the head-to-head say?
Across the last 2 meetings: 0 Mykolaiv win(s), 2 draw(s), 0 Ruh Lviv win(s).
| Date | Score | Competition |
|---|---|---|
| Apr 28, 2018 | Ruh Lviv 3-3 Mykolaiv | Persha Liga |
| Sep 24, 2017 | Mykolaiv 1-1 Ruh Lviv | Persha Liga |
How many goals should we expect?
Mykolaiv score 0.9 and concede 1.0 goals per match over their last 15; Ruh Lviv score 0.9 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mykolaiv | 0.9 | 1.0 | 7 | 4/15 | 5/15 |
| Ruh Lviv | 0.9 | 1.3 | 5 | 5/15 | 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