Arras vs Feignies-Aulnoye: result 1-1 and analysis
National 2 - Group DRegular Season - 12Kick-off on November 24, 2018 at 05:00 PM (UTC)Stade Degouve Brabant, Arras
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What was the result of Arras vs Feignies-Aulnoye?
Arras and Feignies-Aulnoye drew 1-1 on November 24, 2018.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Arras have 3 wins, 6 draws and 6 defeats; Feignies-Aulnoye have 3, 5 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 10, 2018 | Lens II(away) | 2-3 | National 2 - Group D |
| Nov 3, 2018 | Sedan(home) | 1-0 | National 2 - Group D |
| Oct 20, 2018 | Belfort(away) | 0-0 | National 2 - Group D |
| Oct 6, 2018 | Sainte Geneviève(home) | 0-0 | National 2 - Group D |
| Sep 22, 2018 | Schiltigheim(away) | 1-2 | National 2 - Group D |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 10, 2018 | Reims II(home) | 1-0 | National 2 - Group D |
| Nov 3, 2018 | Fleury 91(away) | 2-2 | National 2 - Group D |
| Oct 20, 2018 | Haguenau(home) | 1-1 | National 2 - Group D |
| Oct 6, 2018 | Lille II(away) | 0-3 | National 2 - Group D |
| Sep 22, 2018 | St Maur Lusitanos(home) | 0-1 | National 2 - Group D |
How many goals should we expect?
Arras score 1.2 and concede 1.7 goals per match over their last 15; Feignies-Aulnoye score 1.4 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Arras | 1.2 | 1.7 | 4 | 10/15 | 8/15 |
| Feignies-Aulnoye | 1.4 | 1.3 | 3 | 8/15 | 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 |
|---|---|---|---|---|---|---|---|---|
| 8 | Feignies-Aulnoye | 26 | 9 | 7 | 10 | 28 | 32 | 34 |
A question about Arras vs Feignies-Aulnoye?
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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