Sabah FA vs UiTM FC: result 1-2 and analysis
Premier LeagueRegular Season - 22Kick-off on October 21, 2016 at 12:15 PM (UTC)Likas Stadium, Kota Kinabalu
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What was the result of Sabah FA vs UiTM FC?
UiTM FC won 1-2 on October 21, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sabah FA have 4 wins, 4 draws and 7 defeats; UiTM FC have 1, 3 and 11.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 23, 2016 | Kuantan FA(home) | 2-3 | Premier League |
| Sep 9, 2016 | DRB-Hicom FC(away) | 2-2 | Premier League |
| Aug 23, 2016 | Kuala Lumpur FA(home) | 2-2 | Premier League |
| Aug 16, 2016 | Melaka United(away) | 0-3 | Premier League |
| Aug 5, 2016 | ATM FA(home) | 1-0 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 23, 2016 | Perlis(home) | 2-5 | Premier League |
| Sep 9, 2016 | Kuantan FA(away) | 1-1 | Premier League |
| Aug 23, 2016 | DRB-Hicom FC(home) | 1-2 | Premier League |
| Aug 15, 2016 | Kuala Lumpur FA(away) | 1-2 | Premier League |
| Aug 5, 2016 | Melaka United(home) | 2-3 | Premier League |
What does the head-to-head say?
In the last meeting: 0 Sabah FA wins, 0 draws, 1 UiTM FC win.
| Date | Score | Competition |
|---|---|---|
| Feb 12, 2016 | UiTM FC 4-1 Sabah FA | Premier League |
How many goals should we expect?
Sabah FA score 1.1 and concede 1.5 goals per match over their last 15; UiTM FC score 0.9 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sabah FA | 1.1 | 1.5 | 4 | 8/15 | 9/15 |
| UiTM FC | 0.9 | 2.3 | 2 | 9/15 | 10/15 |
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 |
A question about Sabah FA vs UiTM FC?
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