Gomel II vs Volna: result 0-5 and analysis
1. DivisionRegular Season - 14Kick-off on June 29, 2025 at 01:00 PM (UTC)
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What was the result of Gomel II vs Volna?
Volna won 0-5 on June 29, 2025.
Goalscorers
- 16′G. KukushkinVolna (o.g.)
- 42′D. MatyashVolna
- 52′D. MatyashVolna
- 63′Z. GitselevVolna
- 72′D. MatyashVolna
What is the recent form of both teams?
Over their last 13 matches in all competitions, Gomel II have 2 wins, 3 draws and 8 defeats; Volna have 6, 4 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 22, 2025 | Orsha(home) | 2-5 | 1. Division |
| Jun 14, 2025 | Baranovichi(away) | 1-4 | 1. Division |
| May 31, 2025 | Uni Minsk(away) | 2-1 | 1. Division |
| May 23, 2025 | Osipovichy(home) | 3-2 | 1. Division |
| May 18, 2025 | Niva(away) | 0-1 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 21, 2025 | Baranovichi(home) | 0-2 | 1. Division |
| Jun 13, 2025 | ABFF U19(away) | 3-1 | 1. Division |
| Jun 7, 2025 | Uni Minsk(home) | 1-2 | 1. Division |
| Jun 1, 2025 | Osipovichy(away) | 2-0 | 1. Division |
| May 26, 2025 | Niva(home) | 0-5 | 1. Division |
How many goals should we expect?
Gomel II score 1.1 and concede 2.3 goals per match over their last 13; Volna score 1.7 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Gomel II | 1.1 | 2.3 | 0 | 8/13 | 9/13 |
| Volna | 1.7 | 1.7 | 3 | 9/15 | 10/15 |
Over the last 13 matches in all competitions.
Where do both teams sit in the table?
Gomel II sit 16th in 1. Division (20 points from 21 matches) and Volna sit 8th (31 points from 21 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Volna | 21 | 9 | 4 | 8 | 37 | 37 | 31 |
| 8 | Volna | 12 | 5 | 2 | 5 | 18 | 19 | 17 |
| 15 | Gomel II | 12 | 2 | 4 | 6 | 14 | 18 | 10 |
| 16 | Gomel II | 21 | 5 | 5 | 11 | 28 | 37 | 20 |
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