Forte Taganrog vs Rubin Yalta: result 0-1 and analysis
Second League - Group 1Group 1 - 3Kick-off on April 6, 2024 at 01:00 PM (UTC)Forte Arena Taganrog, Taganrog
Full time
What was the result of Forte Taganrog vs Rubin Yalta?
Rubin Yalta won 0-1 on April 6, 2024.
Goalscorers
- 8′G. SanakoevRubin Yalta
What is the recent form of both teams?
Over their last 15 matches in all competitions, Forte Taganrog have 9 wins, 2 draws and 4 defeats; Rubin Yalta have 8, 4 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 30, 2024 | Alaniya Vladikavkaz II(away) | 5-3 | Second League - Group 1 |
| Jan 18, 2024 | Volgar Astrakhan(away) | 0-1 | Friendlies Clubs |
| Nov 11, 2023 | Rodina Moskva II(home) | 2-0 | Second League A - Division A Silver |
| Nov 5, 2023 | Avangard Kursk(away) | 1-1 | Second League A - Division A Silver |
| Nov 1, 2023 | Ska-khabarovsk(home) | 0-2 | Cup |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 31, 2024 | Stroitel Kamensk-Shakht.(home) | 3-0 | Second League - Group 1 |
| Nov 25, 2023 | Astrakhan(home) | 1-1 | Second League - Group 1 |
| Nov 20, 2023 | Legion Dynamo(away) | 3-1 | Second League - Group 1 |
| Nov 12, 2023 | Mashuk-KMV(home) | 0-1 | Second League - Group 1 |
| Nov 5, 2023 | Astrakhan(away) | 1-1 | Second League - Group 1 |
How many goals should we expect?
Forte Taganrog score 1.7 and concede 1.0 goals per match over their last 15; Rubin Yalta score 1.6 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Forte Taganrog | 1.7 | 1.0 | 6 | 6/15 | 5/15 |
| Rubin Yalta | 1.6 | 0.8 | 5 | 7/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 4 | Rubin Yalta | 20 | 8 | 7 | 5 | 26 | 21 | 31 |
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