Victoria Maryina Gorka vs ML Vitebsk: result 2-3 and analysis
2. DivisionRegular Season - 2Kick-off on May 7, 2016 at 12:00 PM (UTC)
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What was the result of Victoria Maryina Gorka vs ML Vitebsk?
ML Vitebsk won 2-3 on May 7, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Victoria Maryina Gorka have 5 wins, 3 draws and 7 defeats; ML Vitebsk have 1, 5 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 30, 2016 | YuA-Stroy-DYuSSh(away) | 5-1 | 2. Division |
| Nov 14, 2015 | Fc Luch Minsk(home) | 1-4 | 2. Division |
| Nov 7, 2015 | Uzda(away) | 0-2 | 2. Division |
| Oct 31, 2015 | Torpedo Minsk(home) | 1-3 | 2. Division |
| Oct 24, 2015 | Kletsk(away) | 0-2 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 30, 2016 | Zabudova-2007(home) | 2-1 | 2. Division |
| Oct 3, 2015 | Krutogorye(away) | 3-3 | 2. Division |
| Sep 26, 2015 | Krutogorye(home) | 1-1 | 2. Division |
| Sep 19, 2015 | Feniks(away) | 1-1 | 2. Division |
| Sep 12, 2015 | Osipovichy(home) | 0-1 | 2. Division |
What does the head-to-head say?
Across the last 2 meetings: 2 Victoria Maryina Gorka win(s), 0 draw(s), 0 ML Vitebsk win(s).
| Date | Score | Competition |
|---|---|---|
| Aug 15, 2015 | ML Vitebsk 2-3 Victoria Maryina Gorka | 2. Division |
| May 30, 2015 | Victoria Maryina Gorka 1-0 ML Vitebsk | 2. Division |
Last archived meeting: ML Vitebsk vs Victoria Maryina Gorka on Aug 15, 2015
How many goals should we expect?
Victoria Maryina Gorka score 1.4 and concede 1.7 goals per match over their last 15; ML Vitebsk score 1.0 and concede 2.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Victoria Maryina Gorka | 1.4 | 1.7 | 2 | 9/15 | 8/15 |
| ML Vitebsk | 1.0 | 2.2 | 0 | 9/15 | 7/15 |
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