Podillya Khmelnytskyi vs Ruh Lviv: result 0-2 and analysis
Druha LigaRegular Season - 10Kick-off on September 18, 2016 at 02:00 PM (UTC)Stadion Podillia, Khmelnytskyi
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What was the result of Podillya Khmelnytskyi vs Ruh Lviv?
Ruh Lviv won 0-2 on September 18, 2016.
What is the recent form of both teams?
Over their last 9 matches in all competitions, Podillya Khmelnytskyi have 1 win, 1 draw and 7 defeats; Ruh Lviv have 8, 1 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 8, 2016 | Myr(away) | 1-3 | Druha Liga |
| Sep 3, 2016 | Krystal(home) | 0-0 | Druha Liga |
| Aug 26, 2016 | Zhemchuzhyna Odesa(away) | 0-5 | Druha Liga |
| Aug 20, 2016 | Kremin'(home) | 0-2 | Druha Liga |
| Aug 14, 2016 | Nikopol(away) | 0-3 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 13, 2016 | Myr(home) | 1-0 | Druha Liga |
| Sep 8, 2016 | Krystal(away) | 1-1 | Druha Liga |
| Sep 3, 2016 | Zhemchuzhyna Odesa(home) | 0-1 | Druha Liga |
| Aug 26, 2016 | Kremin'(away) | 2-1 | Druha Liga |
| Aug 19, 2016 | Nikopol(home) | 1-0 | Druha Liga |
How many goals should we expect?
Podillya Khmelnytskyi score 0.7 and concede 2.6 goals per match over their last 9; Ruh Lviv score 2.1 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Podillya Khmelnytskyi | 0.7 | 2.6 | 2 | 4/9 | 6/9 |
| Ruh Lviv | 2.1 | 0.9 | 5 | 5/11 | 6/11 |
Over the last 9 matches in all competitions.
Where do both teams sit in the table?
Podillya Khmelnytskyi sit 4th in Druha Liga (13 points from 9 matches) and Ruh Lviv sit 9th (4 points from 9 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Podillya Khmelnytskyi | 9 | 4 | 1 | 4 | 16 | 19 | 13 |
| 9 | Ruh Lviv | 9 | 1 | 1 | 7 | 14 | 17 | 4 |
A question about Podillya Khmelnytskyi vs Ruh Lviv?
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