Muscat vs Saham: result 3-1 and analysis
Professional LeagueRegular Season - 16Kick-off on February 24, 2017 at 04:30 PM (UTC)Sultan Qaboos Sport Complex, Masqaṭ (Muscat)
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What was the result of Muscat vs Saham?
Muscat won 3-1 on February 24, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Muscat have 3 wins, 5 draws and 7 defeats; Saham have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 16, 2017 | Al Nasr(away) | 5-1 | Professional League |
| Feb 3, 2017 | Dhofar(home) | 0-2 | Professional League |
| Dec 2, 2016 | Al Suwaiq(home) | 0-0 | Professional League |
| Nov 28, 2016 | Oman Club(away) | 1-0 | Professional League |
| Nov 23, 2016 | Fanja(away) | 1-3 | Professional League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 21, 2017 | Muharraq(home) | 3-2 | AFC Champions League Two |
| Feb 16, 2017 | Al-Shabab(home) | 1-3 | Professional League |
| Feb 3, 2017 | Sohar(away) | 1-0 | Professional League |
| Dec 2, 2016 | Al-Nahda(away) | 0-3 | Professional League |
| Nov 28, 2016 | Al Oruba(home) | 3-2 | Professional League |
What does the head-to-head say?
Across the last 3 meetings: 0 Muscat win(s), 1 draw(s), 2 Saham win(s).
| Date | Score | Competition |
|---|---|---|
| Sep 27, 2016 | Saham 1-1 Muscat | Professional League |
| Apr 10, 2016 | Muscat 1-2 Saham | Professional League |
| Dec 10, 2015 | Saham 1-0 Muscat | Professional League |
How many goals should we expect?
Muscat score 1.3 and concede 1.5 goals per match over their last 15; Saham score 1.3 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Muscat | 1.3 | 1.5 | 3 | 11/15 | 9/15 |
| Saham | 1.3 | 1.7 | 3 | 8/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 11 | Saham | 26 | 7 | 5 | 14 | 22 | 44 | 26 |
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