Marsa vs Rabat Ajax: result 1-2 and analysis
Challenge LeagueRegular Season - 19Kick-off on February 26, 2017 at 03:15 PM (UTC)Luxol Sports Ground, Pembroke
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What was the result of Marsa vs Rabat Ajax?
Rabat Ajax won 1-2 on February 26, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Marsa have 6 wins, 2 draws and 7 defeats; Rabat Ajax have 4, 2 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 11, 2017 | Gharghur(away) | 0-1 | Challenge League |
| Feb 4, 2017 | Qormi(home) | 1-1 | Challenge League |
| Jan 29, 2017 | Naxxar Lions(away) | 1-3 | Challenge League |
| Jan 22, 2017 | Melita(home) | 0-0 | Challenge League |
| Jan 15, 2017 | Mqabba(away) | 3-2 | Challenge League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Feb 12, 2017 | Lija Athletic(home) | 1-2 | Challenge League |
| Feb 5, 2017 | Pietà Hotspurs(away) | 1-1 | Challenge League |
| Jan 29, 2017 | Senglea Athletic(home) | 0-6 | Challenge League |
| Jan 20, 2017 | Sirens(away) | 0-2 | Challenge League |
| Jan 15, 2017 | Fgura United(home) | 1-1 | Challenge League |
What does the head-to-head say?
In the last meeting: 0 Marsa wins, 0 draws, 1 Rabat Ajax win.
| Date | Score | Competition |
|---|---|---|
| Oct 30, 2016 | Rabat Ajax 1-0 Marsa | Challenge League |
How many goals should we expect?
Marsa score 1.5 and concede 1.7 goals per match over their last 15; Rabat Ajax score 1.2 and concede 2.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Marsa | 1.5 | 1.7 | 2 | 10/15 | 9/15 |
| Rabat Ajax | 1.2 | 2.2 | 2 | 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 |
|---|---|---|---|---|---|---|---|---|
| 7 | Marsa | 22 | 4 | 7 | 11 | 32 | 38 | 17 |
A question about Marsa vs Rabat Ajax?
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