Muscat vs Fanja: result 1-1 and analysis
Professional LeagueRegular Season - 14Kick-off on January 18, 2016 at 03:45 PM (UTC)Al-Seeb Stadium, Seeb
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What was the result of Muscat vs Fanja?
Muscat and Fanja drew 1-1 on January 18, 2016.
What is the recent form of both teams?
Over their last 13 matches in all competitions, Muscat have 1 win, 6 draws and 6 defeats; Fanja have 8, 5 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 26, 2015 | Al Oruba(away) | 0-0 | Professional League |
| Dec 18, 2015 | Al Suwaiq(home) | 1-1 | Professional League |
| Dec 10, 2015 | Saham(away) | 0-1 | Professional League |
| Dec 6, 2015 | Al-Musannah(home) | 1-1 | Professional League |
| Dec 2, 2015 | Dhofar(away) | 1-2 | Professional League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 26, 2015 | Al Suwaiq(away) | 2-3 | Professional League |
| Dec 17, 2015 | Saham(home) | 2-0 | Professional League |
| Dec 10, 2015 | Al-Musannah(away) | 1-0 | Professional League |
| Dec 5, 2015 | Dhofar(home) | 2-1 | Professional League |
| Dec 2, 2015 | Sur(away) | 2-2 | Professional League |
What does the head-to-head say?
In the last meeting: 0 Muscat wins, 0 draws, 1 Fanja win.
| Date | Score | Competition |
|---|---|---|
| Sep 13, 2015 | Fanja 3-0 Muscat | Professional League |
How many goals should we expect?
Muscat score 1.0 and concede 1.6 goals per match over their last 13; Fanja score 1.5 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Muscat | 1.0 | 1.6 | 2 | 9/13 | 7/13 |
| Fanja | 1.5 | 0.8 | 6 | 8/15 | 7/15 |
Over the last 13 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 13 | Fanja | 4 | 0 | 2 | 2 | 0 | 3 | 2 |
A question about Muscat vs Fanja?
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