Melita vs Rabat Ajax: result 1-2 and analysis
Challenge LeagueRegular Season - 21Kick-off on March 11, 2017 at 01:00 PM (UTC)Gianni Bencini Ground, Pembroke
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What was the result of Melita vs Rabat Ajax?
Rabat Ajax won 1-2 on March 11, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Melita have 5 wins, 4 draws and 6 defeats; Rabat Ajax have 3, 2 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 5, 2017 | Gharghur(away) | 2-0 | Challenge League |
| Feb 24, 2017 | Qormi(home) | 1-1 | Challenge League |
| Feb 11, 2017 | Naxxar Lions(away) | 1-1 | Challenge League |
| Feb 5, 2017 | Zebbug Rangers(away) | 1-2 | Challenge League |
| Jan 29, 2017 | Mqabba(home) | 1-2 | Challenge League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 3, 2017 | Mqabba(home) | 1-4 | Challenge League |
| Feb 26, 2017 | Marsa(away) | 2-1 | Challenge League |
| 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 |
What does the head-to-head say?
In the last meeting: 1 Melita win, 0 draws, 0 Rabat Ajax wins.
| Date | Score | Competition |
|---|---|---|
| Nov 18, 2016 | Rabat Ajax 0-1 Melita | Challenge League |
How many goals should we expect?
Melita score 1.1 and concede 1.3 goals per match over their last 15; Rabat Ajax score 1.0 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Melita | 1.1 | 1.3 | 5 | 8/15 | 6/15 |
| Rabat Ajax | 1.0 | 2.3 | 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 | Melita | 5 | 2 | 1 | 2 | 6 | 5 | 7 |
A question about Melita 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