JCAT vs San-Pédro: result 1-2 and analysis
Ligue 1Regular Season - 23Kick-off on May 29, 2017 at 04:00 PM (UTC)Parc des Sports de Treichville, Abidjan
Full time
What was the result of JCAT vs San-Pédro?
San-Pédro won 1-2 on May 29, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, JCAT have 1 win, 3 draws and 11 defeats; San-Pédro have 6, 5 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 22, 2017 | Séwé Sport(home) | 0-3 | Ligue 1 |
| May 7, 2017 | Africa Sports(away) | 1-2 | Ligue 1 |
| Apr 29, 2017 | Denguélé(away) | 1-1 | Ligue 1 |
| Apr 17, 2017 | WAC(away) | 0-1 | Ligue 1 |
| Apr 3, 2017 | Abengourou(home) | 1-2 | Ligue 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 19, 2017 | Tanda(away) | 0-1 | Ligue 1 |
| May 13, 2017 | Abengourou(home) | 0-0 | Ligue 1 |
| May 6, 2017 | ASEC Mimosas(away) | 1-0 | Ligue 1 |
| Apr 29, 2017 | Moossou(away) | 0-1 | Ligue 1 |
| Apr 15, 2017 | AFAD(home) | 1-1 | Ligue 1 |
What does the head-to-head say?
In the last meeting: 0 JCAT wins, 0 draws, 1 San-Pédro win.
| Date | Score | Competition |
|---|---|---|
| Feb 18, 2017 | San-Pédro 2-1 JCAT | Ligue 1 |
How many goals should we expect?
JCAT score 0.6 and concede 1.7 goals per match over their last 15; San-Pédro score 1.1 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| JCAT | 0.6 | 1.7 | 0 | 8/15 | 7/15 |
| San-Pédro | 1.1 | 0.7 | 9 | 3/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | San-Pédro | 3 | 2 | 0 | 1 | 5 | 1 | 6 |
A question about JCAT vs San-Pédro?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.
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