Khimik Svetlogorsk vs FC Dnepr Mogilev: result 2-3 and analysis
1. DivisionRegular Season - 13Kick-off on July 8, 2012 at 03:00 PM (UTC)Stadyen Bumashnik, Svietlahorsk
Full time
What was the result of Khimik Svetlogorsk vs FC Dnepr Mogilev?
FC Dnepr Mogilev won 2-3 on July 8, 2012.
Goalscorers
- 30′O. PatotskiyFC Dnepr Mogilev
- 45′R. ShukelovichKhimik Svetlogorsk
- 53′A. MatveenkoFC Dnepr Mogilev
- 56′R. ShukelovichKhimik Svetlogorsk
- 85′Igors SlesarcuksFC Dnepr Mogilev
What is the recent form of both teams?
Over their last 11 matches in all competitions, Khimik Svetlogorsk have 1 wins, 5 draws and 5 defeats; FC Dnepr Mogilev have 6, 2 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 4, 2012 | Granit(away) | 1-1 | 1. Division |
| Jun 30, 2012 | FC Slutsk(home) | 0-3 | 1. Division |
| Jun 23, 2012 | Volna(away) | 1-0 | 1. Division |
| Jun 17, 2012 | Lida(home) | 0-2 | 1. Division |
| Jun 9, 2012 | FC Vitebsk(away) | 0-5 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 4, 2012 | Polotsk(home) | 5-0 | 1. Division |
| Jun 30, 2012 | Smorgon(away) | 1-2 | 1. Division |
| Jun 23, 2012 | SKVICH(home) | 1-0 | 1. Division |
| Jun 17, 2012 | Byaroza 2010(away) | 1-2 | 1. Division |
| Jun 9, 2012 | Sputnik(home) | 2-1 | 1. Division |
How many goals should we expect?
Khimik Svetlogorsk score 0.5 and concede 1.7 goals per match over their last 11; FC Dnepr Mogilev score 1.7 and concede 0.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Khimik Svetlogorsk | 0.5 | 1.7 | 2 | 4/11 | 3/11 |
| FC Dnepr Mogilev | 1.7 | 0.6 | 6 | 4/11 | 6/11 |
Over the last 11 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | FC Dnepr Mogilev | 34 | 20 | 7 | 7 | 59 | 37 | 67 |
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