Krasnyy-SGAFKST vs Kvant: result 4-1 and analysis
Second League - Group 3Group 3 - 10Kick-off on October 11, 2020 at 12:00 PM (UTC)
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What was the result of Krasnyy-SGAFKST vs Kvant?
Krasnyy-SGAFKST won 4-1 on October 11, 2020.
Goalscorers
- 46′Aleksandr BachevskiyKrasnyy-SGAFKST
- 59′A. MokhammadKrasnyy-SGAFKST
- 69′Vasili MeshkovskiyKrasnyy-SGAFKST
- 79′A. AvagyanKvant
- 86′Vasili MeshkovskiyKrasnyy-SGAFKST (pen.)
What is the recent form of both teams?
Over their last 12 matches in all competitions, Krasnyy-SGAFKST have 4 wins, 4 draws and 4 defeats; Kvant have 4, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 4, 2020 | Khimik-Arsenal(away) | 3-0 | Second League - Group 3 |
| Sep 26, 2020 | Ryazan(home) | 1-0 | Second League - Group 3 |
| Sep 20, 2020 | Saturn Ramenskoye(home) | 1-1 | Second League - Group 3 |
| Sep 12, 2020 | Metallurg Lipetsk(away) | 0-0 | Second League - Group 3 |
| Sep 6, 2020 | Strogino(home) | 0-1 | Second League - Group 3 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 4, 2020 | Metallurg Lipetsk(home) | 1-2 | Second League - Group 3 |
| Sep 27, 2020 | Strogino(away) | 1-1 | Second League - Group 3 |
| Sep 19, 2020 | Salyut-Belgorod(home) | 0-0 | Second League - Group 3 |
| Sep 12, 2020 | Znamya Noginsk(away) | 2-1 | Second League - Group 3 |
| Sep 6, 2020 | Fakel II(home) | 1-0 | Second League - Group 3 |
How many goals should we expect?
Krasnyy-SGAFKST score 1.2 and concede 0.8 goals per match over their last 12; Kvant score 1.1 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Krasnyy-SGAFKST | 1.2 | 0.8 | 5 | 4/12 | 5/12 |
| Kvant | 1.1 | 1.7 | 2 | 7/12 | 7/12 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Kvant | 20 | 1 | 3 | 16 | 21 | 59 | 6 |
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