Strogino vs Kaluga: result 3-1 and analysis
Second League - Group 3Group 3 - 14Kick-off on November 3, 2020 at 11:00 AM (UTC)Stadion Rublevo, Moskva
Full time
What was the result of Strogino vs Kaluga?
Strogino won 3-1 on November 3, 2020.
Goalscorers
- 29′K. ShulgaStrogino
- 45′D. DeminKaluga
- 51′E. ZaerkoStrogino
- 73′G. RodionovStrogino
What is the recent form of both teams?
Over their last 15 matches in all competitions, Strogino have 5 wins, 2 draws and 8 defeats; Kaluga have 6, 3 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 29, 2020 | Avangard Kursk(away) | 0-1 | Second League - Group 3 |
| Oct 23, 2020 | FK Sokol Saratov(home) | 3-2 | Second League - Group 3 |
| Oct 19, 2020 | Metallurg Vidnoye(away) | 2-4 | Second League - Group 3 |
| Oct 11, 2020 | Sakhalin(away) | 1-0 | Second League - Group 3 |
| Oct 5, 2020 | Khimki II(away) | 0-2 | Second League - Group 3 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 29, 2020 | Salyut-Belgorod(home) | 2-3 | Second League - Group 3 |
| Oct 24, 2020 | Znamya Noginsk(away) | 1-1 | Second League - Group 3 |
| Oct 18, 2020 | Fakel II(home) | 4-1 | Second League - Group 3 |
| Oct 11, 2020 | Saturn Ramenskoye(away) | 0-2 | Second League - Group 3 |
| Oct 4, 2020 | Avangard Kursk(away) | 1-1 | Second League - Group 3 |
How many goals should we expect?
Strogino score 1.1 and concede 1.7 goals per match over their last 15; Kaluga score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Strogino | 1.1 | 1.7 | 3 | 8/15 | 7/15 |
| Kaluga | 1.3 | 1.1 | 4 | 8/15 | 6/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | Strogino | 20 | 6 | 4 | 10 | 24 | 33 | 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