Myr vs Podillya Khmelnytskyi: result 3-1 and analysis
Druha LigaRegular Season - 8Kick-off on September 8, 2016 at 02:00 PM (UTC)Stadion Zatys, Hornostayivka
Full time
What was the result of Myr vs Podillya Khmelnytskyi?
Myr won 3-1 on September 8, 2016.
Goalscorers
- 42′Denis BondarenkoMyr
- 45′Alisher YakubovPodillya Khmelnytskyi
- 46′Denis BondarenkoMyr
- 66′A. YaremenkoMyr
What is the recent form of both teams?
Over their last 15 matches in all competitions, Myr have 6 wins, 2 draws and 7 defeats; Podillya Khmelnytskyi have 1, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 26, 2016 | Krystal(away) | 1-0 | Druha Liga |
| Aug 19, 2016 | Zhemchuzhyna Odesa(home) | 0-0 | Druha Liga |
| Aug 14, 2016 | Kremin'(away) | 0-2 | Druha Liga |
| Aug 10, 2016 | Kramatorsk(home) | 1-0 | Cup |
| Aug 5, 2016 | Nikopol(home) | 3-1 | Druha Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| 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 |
| Aug 5, 2016 | Metalurh Zaporizhya(home) | 1-2 | Druha Liga |
How many goals should we expect?
Myr score 0.9 and concede 1.3 goals per match over their last 15; Podillya Khmelnytskyi score 0.6 and concede 2.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Myr | 0.9 | 1.3 | 7 | 4/15 | 6/15 |
| Podillya Khmelnytskyi | 0.6 | 2.5 | 2 | 3/8 | 5/8 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Podillya Khmelnytskyi | 9 | 4 | 1 | 4 | 16 | 19 | 13 |
A question about Myr vs Podillya Khmelnytskyi?
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