Black Forest vs Miscellaneous: result 1-0 and analysis
Premier LeagueRegular Season - 1Kick-off on September 24, 2017 at 02:00 PM (UTC)University of Botswana Stadium, Gaborone
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What was the result of Black Forest vs Miscellaneous?
Black Forest won 1-0 on September 24, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Black Forest have 3 wins, 7 draws and 5 defeats; Miscellaneous have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 25, 2017 | Gilport Lions(away) | 0-0 | Premier League |
| May 20, 2017 | Township Rollers(home) | 0-2 | Premier League |
| May 13, 2017 | Gaborone United(away) | 2-2 | Premier League |
| May 6, 2017 | Galaxy(home) | 2-2 | Premier League |
| May 3, 2017 | Orapa United(away) | 1-2 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 27, 2017 | Green Lovers(away) | 5-0 | Premier League |
| May 20, 2017 | Security Systems(home) | 0-1 | Premier League |
| May 14, 2017 | Centre Chiefs(away) | 0-5 | Premier League |
| May 6, 2017 | Orapa United(home) | 1-2 | Premier League |
| May 2, 2017 | Extension Gunners(home) | 0-1 | Premier League |
What does the head-to-head say?
Across the last 2 meetings: 1 Black Forest win(s), 1 draw(s), 0 Miscellaneous win(s).
| Date | Score | Competition |
|---|---|---|
| Mar 4, 2017 | Miscellaneous 1-2 Black Forest | Premier League |
| Dec 17, 2016 | Black Forest 0-0 Miscellaneous | Premier League |
Last archived meeting: Miscellaneous vs Black Forest on Mar 4, 2017
How many goals should we expect?
Black Forest score 0.9 and concede 1.1 goals per match over their last 15; Miscellaneous score 1.1 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Black Forest | 0.9 | 1.1 | 3 | 8/15 | 5/15 |
| Miscellaneous | 1.1 | 1.3 | 4 | 7/15 | 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