Pknp vs Petaling Jaya City: result 3-1 and analysis
Premier LeagueRegular Season - 12Kick-off on May 5, 2017 at 01:00 PM (UTC)Mini Manjung Stadium, Manjung
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What was the result of Pknp vs Petaling Jaya City?
Pknp won 3-1 on May 5, 2017.
What is the recent form of both teams?
Over their last 11 matches in all competitions, Pknp have 5 wins, 5 draws and 1 defeats; Petaling Jaya City have 2, 0 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 25, 2017 | UiTM FC(away) | 1-1 | Premier League |
| Apr 14, 2017 | Pdrm(home) | 2-1 | Premier League |
| Apr 7, 2017 | Petaling Jaya City(away) | 2-1 | Premier League |
| Mar 3, 2017 | Sabah FA(home) | 1-1 | Premier League |
| Feb 28, 2017 | Johor Darul Tazim II(away) | 1-1 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 25, 2017 | Kuala Lumpur FA(away) | 1-2 | Premier League |
| Apr 14, 2017 | Perlis(away) | 0-2 | Premier League |
| Apr 7, 2017 | Pknp(home) | 1-2 | Premier League |
| Mar 15, 2017 | Sabah FA(home) | 3-1 | Premier League |
| Mar 3, 2017 | UiTM FC(home) | 2-7 | Premier League |
What does the head-to-head say?
Across the last 1 meetings: 1 Pknp win(s), 0 draw(s), 0 Petaling Jaya City win(s).
| Date | Score | Competition |
|---|---|---|
| Apr 7, 2017 | Petaling Jaya City 1-2 Pknp | Premier League |
Last archived meeting: Petaling Jaya City vs Pknp on Apr 7, 2017
How many goals should we expect?
Pknp score 1.2 and concede 0.8 goals per match over their last 11; Petaling Jaya City score 1.7 and concede 2.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Pknp | 1.2 | 0.8 | 4 | 7/11 | 4/11 |
| Petaling Jaya City | 1.7 | 2.7 | 0 | 10/11 | 10/11 |
Over the last 11 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Pknp | 20 | 4 | 5 | 11 | 14 | 37 | 17 |
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