Osipovichy vs SMI Autotrans: result 1-0 and analysis
2. DivisionRegular Season - 12Kick-off on July 6, 2019 at 03:00 PM (UTC)Stadyen Junatstva, Osipovichy
Full time
What was the result of Osipovichy vs SMI Autotrans?
Osipovichy won 1-0 on July 6, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Osipovichy have 7 wins, 2 draws and 6 defeats; SMI Autotrans have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 29, 2019 | Molodechno-DYuSSh 4(away) | 0-3 | 2. Division |
| Jun 22, 2019 | Neman-Agro(home) | 3-0 | 2. Division |
| Jun 15, 2019 | Viktoriya Maryina Horka(home) | 3-1 | 2. Division |
| Jun 12, 2019 | Smolevichi-Sti(home) | 0-1 | Coppa |
| Jun 8, 2019 | Ivatsevichi(home) | 1-0 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 29, 2019 | Uzda(home) | 1-3 | 2. Division |
| Jun 22, 2019 | Oshmyany(away) | 1-5 | 2. Division |
| Jun 15, 2019 | Čist́(home) | 3-2 | 2. Division |
| Jun 12, 2019 | Smorgon(home) | 0-6 | Coppa |
| Jun 8, 2019 | DYuSSh-3 Pinsk(away) | 1-2 | 2. Division |
What does the head-to-head say?
Across the last 2 meetings: 0 Osipovichy wins, 1 draw, 1 SMI Autotrans win.
| Date | Score | Competition |
|---|---|---|
| Aug 18, 2018 | SMI Autotrans 3-2 Osipovichy | 2. Division |
| Apr 29, 2018 | Osipovichy 1-1 SMI Autotrans | 2. Division |
Last archived meeting: SMI Autotrans vs Osipovichy on Aug 18, 2018
How many goals should we expect?
Osipovichy score 1.2 and concede 1.7 goals per match over their last 15; SMI Autotrans score 1.3 and concede 3.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Osipovichy | 1.2 | 1.7 | 5 | 4/15 | 8/15 |
| SMI Autotrans | 1.3 | 3.3 | 1 | 12/15 | 12/15 |
Over the last 15 matches in all competitions.
A question about Osipovichy vs SMI Autotrans?
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How does Footlab AI 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. When bookmakers publish odds for the match, their consensus is built into the calculation: that is what proved most accurate on past matches. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy