FK Neftekhimik vs FK Sokol Saratov: result 2-2 and analysis
First LeagueRegular Season - 14Kick-off on September 26, 2016 at 03:00 PM (UTC)Stadion Neftekhimik, Nizhnekamsk
Full time
What was the result of FK Neftekhimik vs FK Sokol Saratov?
FK Neftekhimik and FK Sokol Saratov drew 2-2 on September 26, 2016.
Goalscorers
- 17′A. BabyrFK Neftekhimik
- 40′Vladimir RomanenkoFK Sokol Saratov
- 72′E. DukhnovFK Neftekhimik
- 80′A. PerchenokFK Sokol Saratov
What is the recent form of both teams?
Over their last 13 matches in all competitions, FK Neftekhimik have 3 wins, 3 draws and 7 defeats; FK Sokol Saratov have 2, 7 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2016 | Luch-Energiya(away) | 0-1 | First League |
| Sep 10, 2016 | Fakel(home) | 1-2 | First League |
| Sep 3, 2016 | Spartak Nalchik(away) | 2-3 | First League |
| Aug 28, 2016 | Kuban(home) | 1-4 | First League |
| Aug 21, 2016 | Volgar Astrakhan(away) | 0-3 | First League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 17, 2016 | Fakel(away) | 2-1 | First League |
| 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 |
How many goals should we expect?
FK Neftekhimik score 0.8 and concede 1.5 goals per match over their last 13; FK Sokol Saratov score 0.9 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| FK Neftekhimik | 0.8 | 1.5 | 5 | 5/13 | 6/13 |
| FK Sokol Saratov | 0.9 | 1.1 | 5 | 8/13 | 5/13 |
Over the last 13 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | FK Neftekhimik | 7 | 2 | 0 | 5 | 4 | 12 | 6 |
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