Sablé vs La Roche sur Yon: prediction and stats
National 3 - Group BPays de la Loire - 6Kick-off on October 24, 2020 at 04:00 PM (UTC)Stade Rémy Lambert, Sablé-sur-Sarthe
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sablé have 4 wins, 7 draws and 4 defeats; La Roche sur Yon have 6, 0 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 12, 2020 | Pouzauges Réaumur(away) | 5-2 | National 3 - Group B |
| Sep 5, 2020 | Laval II(home) | 1-1 | National 3 - Group B |
| Aug 29, 2020 | Changé(away) | 0-2 | National 3 - Group B |
| Mar 7, 2020 | Challans(away) | 0-2 | National 3 - Group B |
| Feb 29, 2020 | La Roche VF(home) | 0-3 | National 3 - Group B |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 10, 2020 | La Châtaigneraie(away) | 3-1 | National 3 - Group B |
| Sep 26, 2020 | Laval II(home) | 1-0 | National 3 - Group B |
| Sep 5, 2020 | Sautron(home) | 2-1 | National 3 - Group B |
| Aug 29, 2020 | Vendée Fontenay(away) | 3-0 | National 3 - Group B |
| Jan 4, 2014 | CA Bastia(home) | 0-3 | Coupe de France |
How many goals should we expect?
Sablé score 1.9 and concede 1.7 goals per match over their last 15; La Roche sur Yon score 2.5 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sablé | 1.9 | 1.7 | 2 | 10/15 | 9/15 |
| La Roche sur Yon | 2.5 | 1.6 | 3 | 3/8 | 7/8 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Sablé sit 14th in National 3 - Group B (27 points from 26 matches) and La Roche sur Yon sit 12th (31 points from 26 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 12 | La Roche sur Yon | 26 | 7 | 10 | 9 | 26 | 36 | 31 |
| 14 | Sablé | 26 | 7 | 7 | 12 | 29 | 40 | 27 |
A question about Sablé vs La Roche sur Yon?
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