UiTM FC vs Sabah FA: result 0-1 and analysis
Premier LeagueRegular Season - 16Kick-off on July 14, 2017 at 01:00 PM (UTC)Stadium Mini UITM, Shah Alam
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What was the result of UiTM FC vs Sabah FA?
Sabah FA won 0-1 on July 14, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, UiTM FC have 5 wins, 8 draws and 2 defeats; Sabah FA have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 10, 2017 | Petaling Jaya City(home) | 3-3 | Premier League |
| Jun 30, 2017 | Pknp(away) | 0-1 | Premier League |
| May 24, 2017 | Terengganu(away) | 1-2 | Premier League |
| May 5, 2017 | Pdrm(home) | 4-3 | Premier League |
| Apr 25, 2017 | Pknp(home) | 1-1 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 10, 2017 | Pknp(home) | 1-3 | Premier League |
| Jun 30, 2017 | Pdrm(away) | 1-0 | Premier League |
| May 24, 2017 | Kuantan FA(away) | 3-3 | Premier League |
| May 5, 2017 | Terengganu(home) | 2-1 | Premier League |
| Apr 25, 2017 | Pdrm(home) | 1-3 | Premier League |
What does the head-to-head say?
Across the last 3 meetings: 3 UiTM FC win(s), 0 draw(s), 0 Sabah FA win(s).
| Date | Score | Competition |
|---|---|---|
| Feb 28, 2017 | Sabah FA 2-3 UiTM FC | Premier League |
| Oct 21, 2016 | Sabah FA 1-2 UiTM FC | Premier League |
| Feb 12, 2016 | UiTM FC 4-1 Sabah FA | Premier League |
How many goals should we expect?
UiTM FC score 2.2 and concede 1.5 goals per match over their last 15; Sabah FA score 1.3 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| UiTM FC | 2.2 | 1.5 | 2 | 12/15 | 9/15 |
| Sabah FA | 1.3 | 2.1 | 1 | 11/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | UiTM FC | 18 | 6 | 2 | 10 | 18 | 25 | 20 |
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