Sirens vs Rabat Ajax: result 2-0 and analysis
Challenge LeagueRegular Season - 15Kick-off on January 20, 2017 at 06:30 PM (UTC)Sirens Stadium, St. Paul's Bay
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What was the result of Sirens vs Rabat Ajax?
Sirens won 2-0 on January 20, 2017.
What is the recent form of both teams?
Over their last 14 matches in all competitions, Sirens have 6 wins, 2 draws and 6 defeats; Rabat Ajax have 4, 2 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 15, 2017 | Gharghur(away) | 4-0 | Challenge League |
| Jan 8, 2017 | Qormi(away) | 0-3 | Challenge League |
| Dec 17, 2016 | Naxxar Lions(home) | 2-2 | Challenge League |
| Dec 11, 2016 | Melita(away) | 2-0 | Challenge League |
| Dec 2, 2016 | Mqabba(home) | 0-1 | Challenge League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jan 15, 2017 | Fgura United(home) | 1-1 | Challenge League |
| Jan 7, 2017 | Vittoriosa Stars(home) | 2-5 | Challenge League |
| Dec 17, 2016 | Zebbug Rangers(home) | 1-5 | Challenge League |
| Dec 10, 2016 | Gharghur(away) | 4-0 | Challenge League |
| Dec 2, 2016 | Qormi(home) | 0-1 | Challenge League |
What does the head-to-head say?
In the last meeting: 1 Sirens win, 0 draws, 0 Rabat Ajax wins.
| Date | Score | Competition |
|---|---|---|
| Sep 17, 2016 | Rabat Ajax 0-3 Sirens | Challenge League |
How many goals should we expect?
Sirens score 1.6 and concede 1.6 goals per match over their last 14; Rabat Ajax score 1.3 and concede 2.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sirens | 1.6 | 1.6 | 5 | 6/14 | 9/14 |
| Rabat Ajax | 1.3 | 2.0 | 2 | 7/14 | 8/14 |
Over the last 14 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Sirens | 3 | 1 | 1 | 1 | 4 | 4 | 4 |
A question about Sirens 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