Jabala vs Horriya: result 2-0 and analysis
Premier LeagueRegular Season - 20Kick-off on March 12, 2021 at 12:00 PM (UTC)Al-Baath Stadium, Jableh
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What was the result of Jabala vs Horriya?
Jabala won 2-0 on March 12, 2021.
Goalscorers
- 79′Osama Haj OmarJabala
- 90′Mahmoud Al BaherJabala (pen.)
What is the recent form of both teams?
Over their last 15 matches in all competitions, Jabala have 4 wins, 7 draws and 4 defeats; Horriya have 1, 3 and 11.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 5, 2021 | Wathba(away) | 0-0 | Premier League |
| Feb 27, 2021 | Al Sahel(home) | 3-1 | Premier League |
| Feb 22, 2021 | Al Wahda(away) | 1-2 | Premier League |
| Feb 17, 2021 | Hottin(home) | 1-2 | Premier League |
| Feb 10, 2021 | Foutoua(away) | 0-0 | Premier League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 5, 2021 | Al-Horgelah(home) | 0-1 | Premier League |
| Feb 28, 2021 | Shorta(away) | 0-1 | Premier League |
| Feb 22, 2021 | Tishreen(home) | 1-3 | Premier League |
| Feb 17, 2021 | Al Ittihad(away) | 0-0 | Premier League |
| Feb 10, 2021 | Wathba(home) | 1-1 | Premier League |
What does the head-to-head say?
In the last meeting: 1 Jabala win, 0 draws, 0 Horriya wins.
| Date | Score | Competition |
|---|---|---|
| Dec 12, 2020 | Horriya 1-2 Jabala | Premier League |
How many goals should we expect?
Jabala score 1.1 and concede 1.1 goals per match over their last 15; Horriya score 0.5 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Jabala | 1.1 | 1.1 | 4 | 10/15 | 7/15 |
| Horriya | 0.5 | 1.5 | 1 | 7/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 13 | Horriya | 1 | 0 | 0 | 1 | 1 | 3 | 0 |
A question about Jabala vs Horriya?
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