Arzew vs CA Batna: result 2-2 and analysis
Ligue 2Regular Season - 23Kick-off on March 11, 2016 at 02:00 PM (UTC)Stade Habib Bouakeul, Oran
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What was the result of Arzew vs CA Batna?
Arzew and CA Batna drew 2-2 on March 11, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Arzew have 5 wins, 2 draws and 8 defeats; CA Batna have 8, 7 and 0.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 4, 2016 | JSM Bejaia(away) | 2-1 | Ligue 2 |
| Feb 26, 2016 | ASO Chlef(home) | 1-0 | Ligue 2 |
| Feb 12, 2016 | US Chaouia(away) | 0-2 | Ligue 2 |
| Feb 5, 2016 | Bordj BOU Arreridj(home) | 1-0 | Ligue 2 |
| Jan 29, 2016 | MC Saida(away) | 0-2 | Ligue 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 4, 2016 | Olympique Medea(home) | 2-0 | Ligue 2 |
| Feb 27, 2016 | El Eulma(away) | 1-1 | Ligue 2 |
| Feb 12, 2016 | Amal BOU Saada(home) | 1-0 | Ligue 2 |
| Feb 5, 2016 | Paradou AC(away) | 0-0 | Ligue 2 |
| Jan 29, 2016 | AIN Fakroun(home) | 1-0 | Ligue 2 |
What does the head-to-head say?
In the last meeting: 0 Arzew wins, 0 draws, 1 CA Batna win.
| Date | Score | Competition |
|---|---|---|
| Oct 16, 2015 | CA Batna 1-0 Arzew | Ligue 2 |
How many goals should we expect?
Arzew score 0.9 and concede 1.5 goals per match over their last 15; CA Batna score 0.9 and concede 0.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Arzew | 0.9 | 1.5 | 4 | 6/15 | 6/15 |
| CA Batna | 0.9 | 0.2 | 12 | 3/15 | 2/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | CA Batna | 5 | 1 | 2 | 2 | 3 | 4 | 5 |
A question about Arzew vs CA Batna?
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