Fanja vs Muscat: result 4-0 and analysis
Professional LeagueRegular Season - 14Kick-off on February 7, 2018 at 04:15 PM (UTC)Al-Seeb Stadium, Seeb
Full time
What was the result of Fanja vs Muscat?
Fanja won 4-0 on February 7, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Fanja have 4 wins, 3 draws and 8 defeats; Muscat have 4, 6 and 5.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 28, 2017 | Al-Nahda(home) | 1-1 | Professional League |
| Nov 24, 2017 | Al Suwaiq(away) | 1-2 | Professional League |
| Nov 3, 2017 | Al Nasr(home) | 1-0 | Professional League |
| Oct 30, 2017 | Al-Shabab(away) | 1-2 | Professional League |
| Oct 26, 2017 | Al-Mudhaibi(home) | 2-1 | Professional League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 28, 2017 | Al Oruba(away) | 1-2 | Professional League |
| Nov 24, 2017 | Mrbat(home) | 3-1 | Professional League |
| Nov 3, 2017 | Al Salam(home) | 3-0 | Professional League |
| Oct 30, 2017 | Dhofar(home) | 2-1 | Professional League |
| Oct 26, 2017 | Al-Nahda(home) | 0-2 | Professional League |
What does the head-to-head say?
Across the last 5 meetings: 3 Fanja win(s), 2 draw(s), 0 Muscat win(s).
| Date | Score | Competition |
|---|---|---|
| Sep 13, 2017 | Muscat 2-2 Fanja | Professional League |
| May 9, 2017 | Muscat 1-3 Fanja | Professional League |
| Nov 23, 2016 | Fanja 3-1 Muscat | Professional League |
| Jan 18, 2016 | Muscat 1-1 Fanja | Professional League |
| Sep 13, 2015 | Fanja 3-0 Muscat | Professional League |
How many goals should we expect?
Fanja score 1.1 and concede 1.5 goals per match over their last 15; Muscat score 1.5 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Fanja | 1.1 | 1.5 | 3 | 10/15 | 10/15 |
| Muscat | 1.5 | 1.3 | 1 | 12/15 | 9/15 |
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