Mqabba vs Rabat Ajax: result 2-0 and analysis
Challenge LeagueRegular Season - 26Kick-off on April 19, 2018 at 05:00 PM (UTC)Victor Tedesco Stadium, Hamrun
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What was the result of Mqabba vs Rabat Ajax?
Mqabba won 2-0 on April 19, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Mqabba have 6 wins, 6 draws and 3 defeats; Rabat Ajax have 0, 1 and 14.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 14, 2018 | Pietà Hotspurs(away) | 1-2 | Challenge League |
| Apr 7, 2018 | Zejtun Corinthians(home) | 1-1 | Challenge League |
| Mar 31, 2018 | Zabbar St. Patrick(home) | 0-0 | Challenge League |
| Mar 17, 2018 | Sirens(away) | 2-2 | Challenge League |
| Mar 11, 2018 | Marsa(home) | 2-1 | Challenge League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 15, 2018 | Zabbar St. Patrick(home) | 0-6 | Challenge League |
| Apr 8, 2018 | Sirens(away) | 0-4 | Challenge League |
| Apr 2, 2018 | Marsa(home) | 2-4 | Challenge League |
| Mar 16, 2018 | San Gwann(away) | 1-5 | Challenge League |
| Mar 11, 2018 | Qrendi(home) | 0-2 | Challenge League |
What does the head-to-head say?
Across the last 3 meetings: 3 Mqabba wins, 0 draws, 0 Rabat Ajax wins.
| Date | Score | Competition |
|---|---|---|
| Jan 7, 2018 | Rabat Ajax 0-3 Mqabba | Challenge League |
| Mar 3, 2017 | Rabat Ajax 1-4 Mqabba | Challenge League |
| Nov 5, 2016 | Mqabba 2-0 Rabat Ajax | Challenge League |
How many goals should we expect?
Mqabba score 1.7 and concede 1.1 goals per match over their last 15; Rabat Ajax score 0.5 and concede 2.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mqabba | 1.7 | 1.1 | 4 | 10/15 | 7/15 |
| Rabat Ajax | 0.5 | 2.9 | 0 | 5/15 | 9/15 |
Over the last 15 matches in all competitions.
A question about Mqabba vs Rabat Ajax?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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