BATE II vs Osipovichy: result 3-1 and analysis
1. DivisionRegular Season - 3Kick-off on April 13, 2025 at 02:00 PM (UTC)
Full time
What was the result of BATE II vs Osipovichy?
BATE II won 3-1 on April 13, 2025.
Goalscorers
- 3′A. SakhonchikBATE II
- 10′N. MirskiyBATE II
- 38′M. KunskiyOsipovichy
- 67′E. RusakovBATE II
What is the recent form of both teams?
Over their last 15 matches in all competitions, BATE II have 6 wins, 3 draws and 6 defeats; Osipovichy have 0, 2 and 13.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 6, 2025 | Niva(home) | 1-1 | 1. Division |
| Mar 29, 2025 | Orsha(home) | 7-2 | 1. Division |
| Nov 23, 2024 | ML Vitebsk(home) | 0-6 | 1. Division |
| Nov 17, 2024 | Niva(away) | 1-6 | 1. Division |
| Nov 10, 2024 | Volna(home) | 1-3 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 5, 2025 | FC Dnepr Mogilev(away) | 2-3 | 1. Division |
| Mar 30, 2025 | Bumprom(home) | 1-1 | 1. Division |
| May 23, 2024 | Miory(away) | 1-2 | Coppa |
| Nov 25, 2023 | FC Dnepr Mogilev(away) | 0-1 | 1. Division |
| Nov 19, 2023 | Niva(home) | 1-4 | 1. Division |
How many goals should we expect?
BATE II score 1.7 and concede 2.2 goals per match over their last 15; Osipovichy score 0.5 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| BATE II | 1.7 | 2.2 | 2 | 9/15 | 11/15 |
| Osipovichy | 0.5 | 2.1 | 1 | 7/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
BATE II sit 17th in 1. Division (17 points from 21 matches) and Osipovichy sit 18th (17 points from 21 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 14 | BATE II | 11 | 2 | 5 | 4 | 16 | 22 | 11 |
| 17 | BATE II | 21 | 4 | 5 | 12 | 29 | 49 | 17 |
| 18 | Osipovichy | 21 | 5 | 2 | 14 | 23 | 51 | 17 |
| 18 | Osipovichy | 11 | 0 | 1 | 10 | 10 | 35 | 1 |
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