Match

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

Miscellaneous
2-1
Black Forest

Full time

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.

Miscellaneous
DateOpponentScoreCompetition
Aug 18, 2018Sankoyo Bush Bucks(away)1-1Premier League
May 22, 2018UF Santos(away)0-2Premier League
May 10, 2018Township Rollers(home)1-3Premier League
May 5, 2018Orapa United(home)1-3Premier League
Apr 28, 2018TAFIC(away)1-0Premier League
Black Forest
DateOpponentScoreCompetition
Aug 22, 2018Township Rollers(home)1-4Premier League
May 23, 2018TAFIC(away)1-2Premier League
May 13, 2018BDF XI(home)1-0Premier League
May 6, 2018UF Santos(away)0-0Premier League
Apr 28, 2018Security Systems(away)0-0Premier League

What does the head-to-head say?

Across the last 4 meetings: 0 Miscellaneous wins, 2 draws, 2 Black Forest wins.

DateScoreCompetition
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 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.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Miscellaneous1.21.349/155/15
Black Forest0.91.366/154/15

Over the last 15 matches in all competitions.

A question about Miscellaneous vs Black Forest?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

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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

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