Security Systems vs Black Forest: result 1-0 and analysis
Premier LeagueRegular Season - 21Kick-off on March 18, 2017 at 02:00 PM (UTC)Molepolole Stadium, Molepolole
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What was the result of Security Systems vs Black Forest?
Security Systems won 1-0 on March 18, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Security Systems have 5 wins, 6 draws and 4 defeats; Black Forest have 5, 7 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 11, 2017 | Police XI(away) | 0-0 | Premier League |
| Mar 4, 2017 | Nico United(home) | 2-0 | Premier League |
| Mar 1, 2017 | Orapa United(home) | 1-0 | Premier League |
| Feb 17, 2017 | Green Lovers(away) | 0-0 | Premier League |
| Feb 11, 2017 | BDF XI(home) | 0-3 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 11, 2017 | Centre Chiefs(home) | 1-1 | Premier League |
| Mar 4, 2017 | Miscellaneous(away) | 2-1 | Premier League |
| Feb 28, 2017 | Sankoyo Bush Bucks(home) | 0-0 | Premier League |
| Feb 18, 2017 | Mahalapye Hotspurs(away) | 0-1 | Premier League |
| Feb 9, 2017 | Extension Gunners(home) | 1-1 | Premier League |
What does the head-to-head say?
Across the last 1 meetings: 0 Security Systems win(s), 1 draw(s), 0 Black Forest win(s).
| Date | Score | Competition |
|---|---|---|
| Dec 7, 2016 | Black Forest 1-1 Security Systems | Premier League |
Last archived meeting: Black Forest vs Security Systems on Dec 7, 2016
How many goals should we expect?
Security Systems score 1.1 and concede 0.9 goals per match over their last 15; Black Forest score 1.1 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Security Systems | 1.1 | 0.9 | 6 | 6/15 | 4/15 |
| Black Forest | 1.1 | 0.9 | 5 | 8/15 | 5/15 |
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