Kuantan FA vs ATM FA: result 0-0 and analysis
Premier LeagueRegular Season - 15Kick-off on July 22, 2016 at 01:00 PM (UTC)Stadium Majlis Perbandaran Selayang, Selayang
Full time
What was the result of Kuantan FA vs ATM FA?
Kuantan FA and ATM FA drew 0-0 on July 22, 2016.
What is the recent form of both teams?
Over their last 13 matches in all competitions, Kuantan FA have 5 wins, 3 draws and 5 defeats; ATM FA have 1, 1 and 11.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 15, 2016 | Sime Darby FC(away) | 4-3 | Premier League |
| May 20, 2016 | Johor Darul Tazim II(away) | 1-4 | Premier League |
| May 17, 2016 | Johor Darul Tazim II(home) | 1-4 | Premier League |
| May 3, 2016 | Pkns FC(away) | 4-4 | Premier League |
| Apr 22, 2016 | Sime Darby FC(home) | 4-2 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 15, 2016 | DRB-Hicom FC(home) | 2-1 | Premier League |
| May 21, 2016 | Melaka United(away) | 1-3 | Premier League |
| May 17, 2016 | Melaka United(home) | 0-6 | Premier League |
| May 3, 2016 | Kuala Lumpur FA(away) | 1-5 | Premier League |
| Apr 22, 2016 | DRB-Hicom FC(away) | 0-4 | Premier League |
What does the head-to-head say?
In the last meeting: 1 Kuantan FA win, 0 draws, 0 ATM FA wins.
| Date | Score | Competition |
|---|---|---|
| Apr 19, 2016 | ATM FA 1-2 Kuantan FA | Premier League |
How many goals should we expect?
Kuantan FA score 1.9 and concede 2.0 goals per match over their last 13; ATM FA score 0.8 and concede 3.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kuantan FA | 1.9 | 2.0 | 2 | 10/13 | 9/13 |
| ATM FA | 0.8 | 3.6 | 0 | 8/13 | 12/13 |
Over the last 13 matches in all competitions.
A question about Kuantan FA vs ATM FA?
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