KAMAZ vs Ural II: result 2-3 and analysis
Second League - Group 4Group 4 - 11Kick-off on October 13, 2020 at 03:30 PM (UTC)Stadion KAMAZ, Naberezhnye Chelny
Full time
What was the result of KAMAZ vs Ural II?
Ural II won 2-3 on October 13, 2020.
Goalscorers
- 12′E. TatarinovUral II
- 25′Ruslan GaliakberovKAMAZ
- 65′A. ShabolinUral II
- 80′Y. KirillovKAMAZ
- 90′E. TatarinovUral II
What is the recent form of both teams?
Over their last 15 matches in all competitions, KAMAZ have 7 wins, 4 draws and 4 defeats; Ural II have 4, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 8, 2020 | Tyumen(away) | 0-1 | Second League - Group 4 |
| Oct 3, 2020 | Zvezda Perm(home) | 3-0 | Second League - Group 4 |
| Sep 24, 2020 | Novosibirsk(away) | 2-2 | Second League - Group 4 |
| Sep 21, 2020 | Dinamo Barnaul(away) | 1-2 | Second League - Group 4 |
| Sep 12, 2020 | Orenburg II(home) | 4-0 | Second League - Group 4 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 3, 2020 | Krylya Sovetov II(away) | 2-1 | Second League - Group 4 |
| Sep 27, 2020 | Tyumen(home) | 1-2 | Second League - Group 4 |
| Sep 20, 2020 | Zvezda Perm(away) | 2-2 | Second League - Group 4 |
| Sep 10, 2020 | Novosibirsk(home) | 1-1 | Second League - Group 4 |
| Sep 7, 2020 | Dinamo Barnaul(home) | 1-0 | Second League - Group 4 |
How many goals should we expect?
KAMAZ score 2.2 and concede 0.9 goals per match over their last 15; Ural II score 1.3 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| KAMAZ | 2.2 | 0.9 | 5 | 8/15 | 10/15 |
| Ural II | 1.3 | 1.4 | 1 | 8/10 | 6/10 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 9 | Ural II | 22 | 5 | 7 | 10 | 34 | 44 | 22 |
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