Paulhan Pézenas vs Toulon: result 3-2 and analysis
National 2 - Group DMatchday 28Kick-off on April 29, 2017 at 04:00 PM (UTC)Stade Municipal, Pézénas
Full time
What was the result of Paulhan Pézenas vs Toulon?
Paulhan Pézenas won 3-2 on April 29, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Paulhan Pézenas have 4 wins, 5 draws and 6 defeats; Toulon have 4, 4 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 22, 2017 | Marignane(away) | 3-4 | National 2 - Group D |
| Apr 15, 2017 | Montpellier II(home) | 2-0 | National 2 - Group D |
| Apr 8, 2017 | Le Pontet US(away) | 1-1 | National 2 - Group D |
| Apr 1, 2017 | Stade Montois(home) | 1-0 | National 2 - Group D |
| Mar 18, 2017 | Rodez(away) | 0-3 | National 2 - Group D |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 22, 2017 | Hyères(home) | 1-0 | National 2 - Group D |
| Apr 15, 2017 | Martigues(away) | 0-0 | National 2 - Group D |
| Apr 8, 2017 | Monaco II(home) | 0-2 | National 2 - Group D |
| Mar 25, 2017 | Olympique Marseille II(away) | 0-2 | National 2 - Group D |
| Mar 18, 2017 | Nice II(home) | 4-5 | National 2 - Group D |
What does the head-to-head say?
In the last meeting: 0 Paulhan Pézenas wins, 1 draw, 0 Toulon wins.
| Date | Score | Competition |
|---|---|---|
| Dec 17, 2016 | Toulon 0-0 Paulhan Pézenas | National 2 - Group D |
Last archived meeting: Toulon vs Paulhan Pézenas on Dec 17, 2016
How many goals should we expect?
Paulhan Pézenas score 1.0 and concede 1.1 goals per match over their last 15; Toulon score 1.2 and concede 1.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Paulhan Pézenas | 1.0 | 1.1 | 7 | 4/15 | 5/15 |
| Toulon | 1.2 | 1.4 | 5 | 6/15 | 7/15 |
Over the last 15 matches in all competitions.
A question about Paulhan Pézenas vs Toulon?
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