Chelyabinsk II vs Uralets Nizhnyi Tagil: result 0-1 and analysis
Second League - Group 4Group 4 - 13Kick-off on July 7, 2025 at 02:00 PM (UTC)
Full time
What was the result of Chelyabinsk II vs Uralets Nizhnyi Tagil?
Uralets Nizhnyi Tagil won 0-1 on July 7, 2025.
Goalscorers
- 40′S. KrotovUralets Nizhnyi Tagil
What is the recent form of both teams?
Over their last 12 matches in all competitions, Chelyabinsk II have 3 wins, 2 draws and 7 defeats; Uralets Nizhnyi Tagil have 8, 2 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 29, 2025 | Rubin Kazan 2(away) | 1-0 | Second League - Group 4 |
| Jun 22, 2025 | Nosta(home) | 1-1 | Second League - Group 4 |
| Jun 14, 2025 | Khimik Dzerzhinsk(away) | 1-2 | Second League - Group 4 |
| Jun 8, 2025 | Krylya Sovetov II(home) | 1-0 | Second League - Group 4 |
| Jun 1, 2025 | Sokol Kazan(away) | 2-1 | Second League - Group 4 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 3, 2025 | KDV(away) | 0-0 | Second League - Group 4 |
| Jun 29, 2025 | Dinamo Barnaul(away) | 3-0 | Second League - Group 4 |
| Jun 22, 2025 | Amkar(away) | 0-1 | Second League - Group 4 |
| Jun 14, 2025 | Ural II(home) | 4-1 | Second League - Group 4 |
| Jun 8, 2025 | Akron II(home) | 2-1 | Second League - Group 4 |
How many goals should we expect?
Chelyabinsk II score 0.8 and concede 2.0 goals per match over their last 12; Uralets Nizhnyi Tagil score 1.7 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Chelyabinsk II | 0.8 | 2.0 | 2 | 6/12 | 6/12 |
| Uralets Nizhnyi Tagil | 1.7 | 1.1 | 5 | 7/15 | 9/15 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | Chelyabinsk II | 22 | 4 | 5 | 13 | 19 | 36 | 17 |
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