Miscellaneous vs Black Forest: result 2-1 and analysis
Premier LeagueRegular Season - 2Kick-off on August 25, 2018 at 01:30 PM (UTC)Itekeng Stadium, Orapa
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What was the result of Miscellaneous vs Black Forest?
Miscellaneous won 2-1 on August 25, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Miscellaneous have 5 wins, 5 draws and 5 defeats; Black Forest have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 18, 2018 | Sankoyo Bush Bucks(away) | 1-1 | Premier League |
| May 22, 2018 | UF Santos(away) | 0-2 | Premier League |
| May 10, 2018 | Township Rollers(home) | 1-3 | Premier League |
| May 5, 2018 | Orapa United(home) | 1-3 | Premier League |
| Apr 28, 2018 | TAFIC(away) | 1-0 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 22, 2018 | Township Rollers(home) | 1-4 | Premier League |
| May 23, 2018 | TAFIC(away) | 1-2 | Premier League |
| May 13, 2018 | BDF XI(home) | 1-0 | Premier League |
| May 6, 2018 | UF Santos(away) | 0-0 | Premier League |
| Apr 28, 2018 | Security Systems(away) | 0-0 | Premier League |
What does the head-to-head say?
Across the last 4 meetings: 0 Miscellaneous win(s), 2 draw(s), 2 Black Forest win(s).
| Date | Score | Competition |
|---|---|---|
| Mar 18, 2018 | Miscellaneous 1-1 Black Forest | Premier League |
| Sep 24, 2017 | Black Forest 1-0 Miscellaneous | Premier League |
| 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 18, 2018
How many goals should we expect?
Miscellaneous score 1.2 and concede 1.3 goals per match over their last 15; Black Forest score 0.9 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Miscellaneous | 1.2 | 1.3 | 4 | 9/15 | 5/15 |
| Black Forest | 0.9 | 1.3 | 6 | 6/15 | 4/15 |
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