Khimik Svetlogorsk vs Neman-Agro: result 2-0 and analysis
1. DivisionRegular Season - 25Kick-off on October 7, 2017 at 12:00 PM (UTC)Stadyen Bumashnik, Svietlahorsk
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What was the result of Khimik Svetlogorsk vs Neman-Agro?
Khimik Svetlogorsk won 2-0 on October 7, 2017.
Goalscorers
- 47′Aleksey PugachKhimik Svetlogorsk
- 75′Aleksey PugachKhimik Svetlogorsk
What is the recent form of both teams?
Over their last 15 matches in all competitions, Khimik Svetlogorsk have 4 wins, 6 draws and 5 defeats; Neman-Agro have 2, 1 and 12.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 30, 2017 | Lokomotiv Gomel(home) | 1-1 | 1. Division |
| Sep 23, 2017 | Torpedo Minsk(away) | 1-0 | 1. Division |
| Sep 17, 2017 | Lida(home) | 1-1 | 1. Division |
| Sep 9, 2017 | Osipovichy(away) | 1-1 | 1. Division |
| Sep 2, 2017 | Belshina(home) | 1-3 | 1. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 30, 2017 | Fc Luch Minsk(home) | 0-5 | 1. Division |
| Sep 23, 2017 | Lokomotiv Gomel(home) | 1-2 | 1. Division |
| Sep 16, 2017 | Granit(home) | 0-5 | 1. Division |
| Sep 9, 2017 | Torpedo Minsk(away) | 0-5 | 1. Division |
| Sep 2, 2017 | Orsha(home) | 3-6 | 1. Division |
What does the head-to-head say?
Across the last 1 meetings: 0 Khimik Svetlogorsk win(s), 0 draw(s), 1 Neman-Agro win(s).
| Date | Score | Competition |
|---|---|---|
| Jun 10, 2017 | Neman-Agro 2-0 Khimik Svetlogorsk | 1. Division |
Last archived meeting: Neman-Agro vs Khimik Svetlogorsk on Jun 10, 2017
How many goals should we expect?
Khimik Svetlogorsk score 1.3 and concede 1.9 goals per match over their last 15; Neman-Agro score 0.9 and concede 3.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Khimik Svetlogorsk | 1.3 | 1.9 | 3 | 10/15 | 8/15 |
| Neman-Agro | 0.9 | 3.2 | 1 | 7/15 | 12/15 |
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