Biolog vs Chayka: result 0-2 and analysis
Second League - Group 1Group 1 - 25Kick-off on April 22, 2023 at 10:00 AM (UTC)Stadion Biolog, Progress
Full time
What was the result of Biolog vs Chayka?
Chayka won 0-2 on April 22, 2023.
Goalscorers
- 29′D. SadovChayka
- 36′M. KolmakovChayka
What is the recent form of both teams?
Over their last 15 matches in all competitions, Biolog have 7 wins, 4 draws and 4 defeats; Chayka have 9, 4 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 15, 2023 | SKA Rostov(away) | 1-3 | Second League - Group 1 |
| Apr 8, 2023 | Dinamo Stavropol(home) | 0-0 | Second League - Group 1 |
| Apr 1, 2023 | Chernomorets(away) | 2-2 | Second League - Group 1 |
| Mar 25, 2023 | Legion Dynamo(home) | 3-0 | Second League - Group 1 |
| Mar 18, 2023 | Druzhba(home) | 0-1 | Second League - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 15, 2023 | Rotor Volgograd(home) | 0-0 | Second League - Group 1 |
| Apr 8, 2023 | Spartak Nalchik(away) | 2-1 | Second League - Group 1 |
| Apr 1, 2023 | Forte Taganrog(home) | 1-3 | Second League - Group 1 |
| Mar 24, 2023 | Essentuki(away) | 7-1 | Second League - Group 1 |
| Mar 18, 2023 | Mashuk-KMV(home) | 2-0 | Second League - Group 1 |
What does the head-to-head say?
Across the last 3 meetings: 0 Biolog win(s), 1 draw(s), 2 Chayka win(s).
| Date | Score | Competition |
|---|---|---|
| Oct 15, 2022 | Chayka 1-0 Biolog | Second League - Group 1 |
| Mar 19, 2022 | Biolog 1-1 Chayka | Second League - Group 1 |
| Aug 29, 2021 | Chayka 2-1 Biolog | Second League - Group 1 |
How many goals should we expect?
Biolog score 1.5 and concede 0.9 goals per match over their last 15; Chayka score 1.9 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Biolog | 1.5 | 0.9 | 6 | 7/15 | 8/15 |
| Chayka | 1.9 | 0.8 | 8 | 7/15 | 8/15 |
Over the last 15 matches in all competitions.
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