Druzhba vs SKA Rostov: result 1-3 and analysis
Second League - Group 1Group 1 - 10Kick-off on October 11, 2020 at 02:00 PM (UTC)Adygeyskiy Respublikanskiy Stadion Druzhba, Maykop
Full time
What was the result of Druzhba vs SKA Rostov?
SKA Rostov won 1-3 on October 11, 2020.
Goalscorers
- 37′Gennadi KozlovSKA Rostov
- 44′K. YushkoSKA Rostov
- 57′268928SKA Rostov
- 69′A. KonovDruzhba
What is the recent form of both teams?
Over their last 11 matches in all competitions, Druzhba have 4 wins, 2 draws and 5 defeats; SKA Rostov have 5, 2 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 27, 2020 | Forte Taganrog(away) | 2-1 | Second League - Group 1 |
| Sep 20, 2020 | Mashuk-KMV(home) | 1-1 | Second League - Group 1 |
| Sep 14, 2020 | Tuapse(away) | 2-1 | Second League - Group 1 |
| Sep 6, 2020 | Inter Cherkessk(home) | 3-3 | Second League - Group 1 |
| Aug 29, 2020 | Urozhay(away) | 0-2 | Second League - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 4, 2020 | Forte Taganrog(home) | 2-1 | Second League - Group 1 |
| Sep 27, 2020 | Mashuk-KMV(away) | 1-3 | Second League - Group 1 |
| Sep 21, 2020 | Tuapse(away) | 1-1 | Second League - Group 1 |
| Sep 11, 2020 | Inter Cherkessk(away) | 4-1 | Second League - Group 1 |
| Sep 6, 2020 | Urozhay(home) | 3-2 | Second League - Group 1 |
How many goals should we expect?
Druzhba score 1.2 and concede 1.8 goals per match over their last 11; SKA Rostov score 1.4 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Druzhba | 1.2 | 1.8 | 1 | 6/11 | 7/11 |
| SKA Rostov | 1.4 | 1.5 | 2 | 8/12 | 7/12 |
Over the last 11 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 9 | Druzhba | 19 | 7 | 6 | 6 | 25 | 21 | 27 |
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