Match

Black Forest vs Miscellaneous: result 1-2 and analysis

Premier LeagueRegular Season - 17Kick-off on January 19, 2019 at 01:45 PM (UTC)University of Botswana Stadium, Gaborone

Black Forest
1-2
Miscellaneous

Full time

What was the result of Black Forest vs Miscellaneous?

Miscellaneous won 1-2 on January 19, 2019.

What is the recent form of both teams?

Over their last 15 matches in all competitions, Black Forest have 2 wins, 3 draws and 10 defeats; Miscellaneous have 4, 5 and 6.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Black Forest
DateOpponentScoreCompetition
Jan 12, 2019BDF XI(away)0-3Premier League
Dec 16, 2018Security Systems(away)0-4Premier League
Dec 13, 2018Prisons XI(home)1-2Premier League
Nov 27, 2018Gaborone United(away)0-2Premier League
Nov 10, 2018BR Highlanders(home)1-1Premier League
Miscellaneous
DateOpponentScoreCompetition
Jan 12, 2019Shooting Stars(home)0-0Premier League
Dec 13, 2018Security Systems(home)0-0Premier League
Dec 1, 2018Prisons XI(away)3-1Premier League
Nov 10, 2018Gaborone United(home)2-3Premier League
Nov 7, 2018Township Rollers(home)0-1Premier League

What does the head-to-head say?

Across the last 5 meetings: 2 Black Forest win(s), 2 draw(s), 1 Miscellaneous win(s).

DateScoreCompetition
Aug 25, 2018Miscellaneous 2-1 Black ForestPremier League
Mar 18, 2018Miscellaneous 1-1 Black ForestPremier League
Sep 24, 2017Black Forest 1-0 MiscellaneousPremier League
Mar 4, 2017Miscellaneous 1-2 Black ForestPremier League
Dec 17, 2016Black Forest 0-0 MiscellaneousPremier League

Last archived meeting: Miscellaneous vs Black Forest on Aug 25, 2018

How many goals should we expect?

Black Forest score 0.9 and concede 1.9 goals per match over their last 15; Miscellaneous score 1.0 and concede 1.1.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Black Forest0.91.928/158/15
Miscellaneous1.01.166/156/15

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

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