TOM Tomsk vs Fakel: result 2-0 and analysis
First LeagueRegular Season - 1Kick-off on July 17, 2018 at 12:00 PM (UTC)Stadion Trud, Tomsk
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What was the result of TOM Tomsk vs Fakel?
TOM Tomsk won 2-0 on July 17, 2018.
Goalscorers
- 13′I. KukharchukTOM Tomsk
- 88′I. KukharchukTOM Tomsk
What is the recent form of both teams?
Over their last 15 matches in all competitions, TOM Tomsk have 4 wins, 5 draws and 6 defeats; Fakel have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 12, 2018 | Kuban(away) | 3-3 | First League |
| May 6, 2018 | Rotor Volgograd(home) | 1-0 | First League |
| May 2, 2018 | Fakel(away) | 1-0 | First League |
| Apr 28, 2018 | Zenit 2(home) | 1-2 | First League |
| Apr 21, 2018 | Enisey(away) | 2-3 | First League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 12, 2018 | Volgar Astrakhan(home) | 2-1 | First League |
| May 6, 2018 | Khimki(away) | 3-1 | First League |
| May 2, 2018 | TOM Tomsk(home) | 0-1 | First League |
| Apr 28, 2018 | Krylia Sovetov(away) | 1-2 | First League |
| Apr 21, 2018 | Nizhny Novgorod(home) | 4-1 | First League |
What does the head-to-head say?
Across the last 2 meetings: 2 TOM Tomsk win(s), 0 draw(s), 0 Fakel win(s).
| Date | Score | Competition |
|---|---|---|
| May 2, 2018 | Fakel 0-1 TOM Tomsk | First League |
| Oct 14, 2017 | TOM Tomsk 1-0 Fakel | First League |
How many goals should we expect?
TOM Tomsk score 1.1 and concede 1.5 goals per match over their last 15; Fakel score 0.9 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| TOM Tomsk | 1.1 | 1.5 | 5 | 8/15 | 7/15 |
| Fakel | 0.9 | 1.5 | 2 | 6/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Fakel | 34 | 20 | 8 | 6 | 44 | 22 | 68 |
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