AFAD vs Bassam: result 0-2 and analysis
Ligue 1Regular Season - 6Kick-off on October 18, 2018 at 03:30 PM (UTC)Stade Robert Champroux, Abidjan
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What was the result of AFAD vs Bassam?
Bassam won 0-2 on October 18, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, AFAD have 4 wins, 8 draws and 3 defeats; Bassam have 5, 4 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 7, 2018 | ASEC Mimosas(away) | 2-1 | Ligue 1 |
| Sep 29, 2018 | Moossou(home) | 3-0 | Ligue 1 |
| Sep 22, 2018 | Sporting Gagnoa(home) | 0-0 | Ligue 1 |
| Sep 15, 2018 | San-Pédro(away) | 1-1 | Ligue 1 |
| Sep 10, 2018 | Lys Sassandra(away) | 0-0 | Ligue 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 6, 2018 | Racing d'Abidjan(away) | 0-3 | Ligue 1 |
| Sep 30, 2018 | WAC(home) | 1-1 | Ligue 1 |
| Sep 22, 2018 | San-Pédro(away) | 1-1 | Ligue 1 |
| Sep 15, 2018 | SOA(home) | 1-4 | Ligue 1 |
| Sep 7, 2018 | Africa Sports(home) | 2-0 | Ligue 1 |
What does the head-to-head say?
Across the last 2 meetings: 0 AFAD wins, 0 draws, 2 Bassam wins.
| Date | Score | Competition |
|---|---|---|
| Jun 3, 2018 | Bassam 3-0 AFAD | Ligue 1 |
| Dec 28, 2017 | AFAD 1-3 Bassam | Ligue 1 |
How many goals should we expect?
AFAD score 0.9 and concede 0.9 goals per match over their last 15; Bassam score 1.1 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| AFAD | 0.9 | 0.9 | 7 | 7/15 | 7/15 |
| Bassam | 1.1 | 1.4 | 5 | 7/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 11 | AFAD | 3 | 0 | 2 | 1 | 3 | 4 | 2 |
A question about AFAD vs Bassam?
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