Fakel vs FK Sokol Saratov: result 1-2 and analysis
First LeagueRegular Season - 13Kick-off on September 17, 2016 at 03:00 PM (UTC)Central'nyi Stadion Profsoyuzov, Voronezh
Full time
What was the result of Fakel vs FK Sokol Saratov?
FK Sokol Saratov won 1-2 on September 17, 2016.
Goalscorers
- 14′V. GalyshFK Sokol Saratov
- 37′V. GalyshFK Sokol Saratov
- 82′Mikhail BiryukovFakel
What is the recent form of both teams?
Over their last 12 matches in all competitions, Fakel have 6 wins, 4 draws and 2 defeats; FK Sokol Saratov have 1, 7 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 10, 2016 | FK Neftekhimik(away) | 2-1 | First League |
| Sep 3, 2016 | Kuban(away) | 0-0 | First League |
| Aug 28, 2016 | Mordovia Saransk(home) | 1-2 | First League |
| Aug 21, 2016 | Sibir(away) | 1-1 | First League |
| Aug 17, 2016 | Khimki(home) | 2-0 | First League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 10, 2016 | Kuban(away) | 0-0 | First League |
| Sep 3, 2016 | Mordovia Saransk(away) | 0-0 | First League |
| Aug 28, 2016 | Sibir(home) | 1-1 | First League |
| Aug 21, 2016 | Khimki(away) | 0-0 | First League |
| Aug 17, 2016 | Ska-khabarovsk(home) | 2-3 | First League |
How many goals should we expect?
Fakel score 1.4 and concede 0.8 goals per match over their last 12; FK Sokol Saratov score 0.8 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Fakel | 1.4 | 0.8 | 5 | 7/12 | 5/12 |
| FK Sokol Saratov | 0.8 | 1.1 | 5 | 7/12 | 4/12 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
Fakel sit 2nd in First League (68 points from 34 matches) and FK Sokol Saratov sit 17th (26 points from 34 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Fakel | 34 | 20 | 8 | 6 | 44 | 22 | 68 |
| 17 | FK Sokol Saratov | 34 | 5 | 11 | 18 | 16 | 44 | 26 |
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