SKVICH vs FC Vitebsk: result 1-0 and analysis
1. DivisionMatchday 5Kick-off on May 19, 2012 at 04:00 PM (UTC)SOK Olympijskij, Minsk
Full time
What was the result of SKVICH vs FC Vitebsk?
SKVICH won 1-0 on May 19, 2012.
Goalscorers
- 90′Denis SashchekoSKVICH
Official lineup for SKVICH vs FC Vitebsk
The starting elevens fielded at kick-off.
SKVICH
- DDenis Sashcheko
- VVitaly Shepetovskiy
- AAleksandr Mikhnovets
- VVladimir Margulets
- SS. Shumanov
- PP. Shmigero
- YY. Markhel
- AAleksey Belousov
- VVladimir Shibeko
- DD. Lekhavitskiy
- VVitali Makauchyk
FC Vitebsk
- DD. Gomza
- AAndrei Baranok
- AAleksandr Degterev
- MMarat Voronov
- AA. Pakulin
- VV. Krasnov
- AAndrey Raspopov
- II. Sadovnichiy
- AA. Poznyak
- AA. Skitov
- YYuriy Vasyutin
What is the recent form of both teams?
Over their last 4 matches in all competitions, SKVICH have 3 wins, 0 draws and 1 defeat; FC Vitebsk have 2, 1 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 11, 2012 | DSK Gomel(away) | 3-0 | 1. Division |
| May 5, 2012 | Rudensk(home) | 2-1 | 1. Division |
| Apr 28, 2012 | Gorodeya(away) | 0-1 | 1. Division |
| Apr 21, 2012 | Khimik Svetlogorsk(home) | 2-0 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 11, 2012 | Byaroza 2010(home) | 2-1 | 1. Division |
| May 5, 2012 | Sputnik(away) | 3-0 | 1. Division |
| Apr 28, 2012 | FC Dnepr Mogilev(home) | 0-0 | 1. Division |
| Apr 21, 2012 | Granit(away) | 0-1 | 1. Division |
How many goals should we expect?
SKVICH score 1.8 and concede 0.5 goals per match over their last 4; FC Vitebsk score 1.3 and concede 0.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| SKVICH | 1.8 | 0.5 | 2 | 1/4 | 2/4 |
| FC Vitebsk | 1.3 | 0.5 | 2 | 1/4 | 2/4 |
Over the last 4 matches in all competitions.
A question about SKVICH vs FC Vitebsk?
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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