Ivatsevichi vs Molodechno-DYuSSh 4: result 3-0 and analysis
2. DivisionRegular Season - 12Kick-off on July 6, 2019 at 12:00 PM (UTC)Klenovka Arena, Ivatsevichy
Full time
What was the result of Ivatsevichi vs Molodechno-DYuSSh 4?
Ivatsevichi won 3-0 on July 6, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Ivatsevichi have 6 wins, 1 draws and 8 defeats; Molodechno-DYuSSh 4 have 9, 1 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 29, 2019 | Neman-Agro(away) | 3-0 | 2. Division |
| Jun 22, 2019 | Viktoriya Maryina Horka(home) | 4-0 | 2. Division |
| Jun 12, 2019 | Ruh Brest(home) | 2-3 | Coppa |
| Jun 8, 2019 | Osipovichy(away) | 0-1 | 2. Division |
| Jun 1, 2019 | Uzda(home) | 3-0 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 29, 2019 | Osipovichy(home) | 3-0 | 2. Division |
| Jun 22, 2019 | Uzda(away) | 1-2 | 2. Division |
| Jun 15, 2019 | Oshmyany(home) | 1-5 | 2. Division |
| Jun 12, 2019 | Arsenal(home) | 0-5 | Coppa |
| Jun 8, 2019 | Čist́(away) | 2-1 | 2. Division |
What does the head-to-head say?
Across the last 2 meetings: 1 Ivatsevichi win(s), 0 draw(s), 1 Molodechno-DYuSSh 4 win(s).
| Date | Score | Competition |
|---|---|---|
| Oct 6, 2018 | Ivatsevichi 2-3 Molodechno-DYuSSh 4 | 2. Division |
| Jun 23, 2018 | Molodechno-DYuSSh 4 0-1 Ivatsevichi | 2. Division |
Last archived meeting: Ivatsevichi vs Molodechno-DYuSSh 4 on Oct 6, 2018
How many goals should we expect?
Ivatsevichi score 2.0 and concede 2.1 goals per match over their last 15; Molodechno-DYuSSh 4 score 2.3 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Ivatsevichi | 2.0 | 2.1 | 4 | 7/15 | 12/15 |
| Molodechno-DYuSSh 4 | 2.3 | 1.7 | 3 | 10/15 | 13/15 |
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