Al Oruba vs Saham: result 2-1 and analysis
Professional LeagueRegular Season - 21Kick-off on April 12, 2013 at 03:15 PM (UTC)Sur Sports Complex
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What was the result of Al Oruba vs Saham?
Al Oruba won 2-1 on April 12, 2013.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Al Oruba have 4 wins, 8 draws and 3 defeats; Saham 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 |
|---|---|---|---|
| Mar 29, 2013 | Al Seeb(away) | 0-0 | Professional League |
| Mar 17, 2013 | Al Shabab(home) | 2-0 | Professional League |
| Mar 1, 2013 | Al Nasr(away) | 0-0 | Professional League |
| Feb 21, 2013 | Al-Nahda(home) | 3-1 | Professional League |
| Feb 16, 2013 | Oman Club(away) | 1-0 | Professional League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 29, 2013 | Al Suwaiq(home) | 1-1 | Professional League |
| Mar 14, 2013 | Al Musannah(away) | 1-0 | Professional League |
| Mar 1, 2013 | Al Taleea(home) | 0-2 | Professional League |
| Feb 21, 2013 | Dhofar(away) | 0-0 | Professional League |
| Feb 17, 2013 | Fanja(home) | 5-0 | Professional League |
What does the head-to-head say?
In the last meeting: 0 Al Oruba wins, 0 draws, 1 Saham win.
| Date | Score | Competition |
|---|---|---|
| Dec 12, 2012 | Saham 1-0 Al Oruba | Professional League |
How many goals should we expect?
Al Oruba score 0.9 and concede 0.7 goals per match over their last 15; Saham score 1.4 and concede 0.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Al Oruba | 0.9 | 0.7 | 6 | 6/15 | 2/15 |
| Saham | 1.4 | 0.5 | 10 | 4/15 | 6/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Saham | 5 | 3 | 0 | 2 | 5 | 5 | 9 |
A question about Al Oruba vs Saham?
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