Naters vs Olympique de Genève: result 0-0 and analysis
1. Liga Classic - Group 1Group 1 - 10Kick-off on October 12, 2019 at 03:00 PM (UTC)Sportanlage Stapfen, Naters
Full time
What was the result of Naters vs Olympique de Genève?
Naters and Olympique de Genève drew 0-0 on October 12, 2019.
What is the recent form of both teams?
Over their last 9 matches in all competitions, Naters have 6 wins, 0 draws and 3 defeats; Olympique de Genève have 4, 3 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 28, 2019 | Lancy(away) | 2-0 | 1. Liga Classic - Group 1 |
| Sep 21, 2019 | Young Boys II(home) | 3-1 | 1. Liga Classic - Group 1 |
| Sep 14, 2019 | Lausanne Sport II(away) | 0-1 | 1. Liga Classic - Group 1 |
| Sep 7, 2019 | Vevey Sports(home) | 3-1 | 1. Liga Classic - Group 1 |
| Aug 31, 2019 | Terre Sainte(away) | 3-1 | 1. Liga Classic - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 28, 2019 | Young Boys II(away) | 0-0 | 1. Liga Classic - Group 1 |
| Sep 22, 2019 | Vevey Sports(home) | 1-0 | 1. Liga Classic - Group 1 |
| Sep 18, 2019 | La Chaux-de-Fonds(away) | 1-2 | 1. Liga Classic - Group 1 |
| Sep 14, 2019 | Bavois(home) | 1-2 | Schweizer Cup |
| Sep 8, 2019 | Meyrin(home) | 1-2 | 1. Liga Classic - Group 1 |
How many goals should we expect?
Naters score 1.8 and concede 0.9 goals per match over their last 9; Olympique de Genève score 1.5 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Naters | 1.8 | 0.9 | 3 | 4/9 | 5/9 |
| Olympique de Genève | 1.5 | 1.2 | 4 | 7/11 | 7/11 |
Over the last 9 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Naters | 9 | 4 | 2 | 3 | 20 | 23 | 14 |
A question about Naters vs Olympique de Genève?
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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