Al Faisaly vs Sahab: result 4-0 and analysis
LeagueRegular Season - 22Kick-off on May 6, 2017 at 01:30 PM (UTC)Amman International Stadium, Amman
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What was the result of Al Faisaly vs Sahab?
Al Faisaly won 4-0 on May 6, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Al Faisaly have 9 wins, 5 draws and 1 defeat; Sahab have 1, 4 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 29, 2017 | Al Buqa'a(away) | 2-0 | League |
| Apr 21, 2017 | Al Hussein(home) | 1-1 | League |
| Apr 15, 2017 | Al Sareeh(away) | 2-1 | League |
| Apr 8, 2017 | Al Wihdat(home) | 2-1 | League |
| Apr 1, 2017 | Shabab Al Ordon(home) | 5-0 | League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 27, 2017 | Al Ahli(home) | 1-3 | League |
| Apr 21, 2017 | Mansheyat(away) | 1-2 | League |
| Apr 15, 2017 | Al Ramtha(home) | 0-3 | League |
| Apr 8, 2017 | Al Jazeera(away) | 0-0 | League |
| Apr 1, 2017 | That Ras(home) | 0-2 | League |
What does the head-to-head say?
In the last meeting: 0 Al Faisaly wins, 1 draw, 0 Sahab wins.
| Date | Score | Competition |
|---|---|---|
| Jan 14, 2017 | Sahab 1-1 Al Faisaly | League |
How many goals should we expect?
Al Faisaly score 1.6 and concede 0.6 goals per match over their last 15; Sahab score 0.5 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Al Faisaly | 1.6 | 0.6 | 8 | 7/15 | 6/15 |
| Sahab | 0.5 | 1.5 | 3 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Al Faisaly | 4 | 3 | 1 | 0 | 7 | 0 | 10 |
A question about Al Faisaly vs Sahab?
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