AFAD vs Moossou: result 2-0 and analysis
Ligue 1Regular Season - 25Kick-off on June 17, 2017 at 03:30 PM (UTC)Stade Robert Champroux, Abidjan
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What was the result of AFAD vs Moossou?
AFAD won 2-0 on June 17, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, AFAD have 4 wins, 7 draws and 4 defeats; Moossou have 4, 3 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 4, 2017 | Séwé Sport(home) | 1-0 | Ligue 1 |
| May 27, 2017 | Sporting Gagnoa(away) | 1-0 | Ligue 1 |
| May 22, 2017 | Abengourou(home) | 0-0 | Ligue 1 |
| May 14, 2017 | ASEC Mimosas(away) | 3-3 | Ligue 1 |
| May 6, 2017 | Tanda(home) | 0-0 | Ligue 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 3, 2017 | Denguélé(away) | 1-0 | Ligue 1 |
| Jun 1, 2017 | JCAT(home) | 2-0 | Ligue 1 |
| May 27, 2017 | Africa Sports(home) | 0-0 | Ligue 1 |
| May 21, 2017 | Stade d'Abidjan(home) | 1-2 | Ligue 1 |
| May 6, 2017 | Séwé Sport(away) | 1-2 | Ligue 1 |
What does the head-to-head say?
In the last meeting: 1 AFAD win, 0 draws, 0 Moossou wins.
| Date | Score | Competition |
|---|---|---|
| Mar 3, 2017 | Moossou 0-3 AFAD | Ligue 1 |
How many goals should we expect?
AFAD score 0.9 and concede 0.9 goals per match over their last 15; Moossou score 0.9 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| AFAD | 0.9 | 0.9 | 6 | 5/15 | 3/15 |
| Moossou | 0.9 | 1.2 | 5 | 6/15 | 6/15 |
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 | AFAD | 3 | 0 | 2 | 1 | 3 | 4 | 2 |
A question about AFAD vs Moossou?
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