Rubin Kazan 2 vs Khimik Vurnary: result 0-2 and analysis
Second League - Group 4Group 4 - 8Kick-off on September 3, 2023 at 02:00 PM (UTC)Stadion Rubin, Kazan'
Full time
What was the result of Rubin Kazan 2 vs Khimik Vurnary?
Khimik Vurnary won 0-2 on September 3, 2023.
Goalscorers
- 25′D. SokolovKhimik Vurnary
- 56′V. FominKhimik Vurnary
What is the recent form of both teams?
Over their last 7 matches in all competitions, Rubin Kazan 2 have 2 wins, 4 draws and 1 defeats; Khimik Vurnary have 8, 5 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2023 | Uralets Nizhnyi Tagil(away) | 1-0 | Second League - Group 4 |
| Aug 19, 2023 | Dinamo Barnaul(home) | 1-1 | Second League - Group 4 |
| Aug 13, 2023 | Torpedo Miass(away) | 0-4 | Second League - Group 4 |
| Aug 6, 2023 | Nosta(home) | 0-0 | Second League - Group 4 |
| Jul 29, 2023 | Orenburg II(home) | 2-2 | Second League - Group 4 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 23, 2023 | Zenit Penza(home) | 1-1 | Cup |
| Aug 19, 2023 | Ural II(away) | 2-0 | Second League - Group 4 |
| Aug 13, 2023 | Akron II(home) | 2-0 | Second League - Group 4 |
| Aug 6, 2023 | Orenburg II(away) | 0-0 | Second League - Group 4 |
| Jul 29, 2023 | Uralets Nizhnyi Tagil(home) | 0-0 | Second League - Group 4 |
How many goals should we expect?
Rubin Kazan 2 score 1.0 and concede 1.1 goals per match over their last 7; Khimik Vurnary score 1.5 and concede 0.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rubin Kazan 2 | 1.0 | 1.1 | 3 | 3/7 | 2/7 |
| Khimik Vurnary | 1.5 | 0.6 | 7 | 7/15 | 6/15 |
Over the last 7 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Rubin Kazan 2 | 22 | 4 | 8 | 10 | 25 | 35 | 20 |
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