Matran vs Düdingen: result 1-1 and analysis
2. Liga Interregional - Group 2Group 2 - 13Kick-off on November 12, 2022 at 05:00 PM (UTC)
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What was the result of Matran vs Düdingen?
Matran and Düdingen drew 1-1 on November 12, 2022.
What is the recent form of both teams?
Over their last 12 matches in all competitions, Matran have 1 win, 3 draws and 8 defeats; Düdingen have 9, 2 and 4.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 5, 2022 | Tavannes / Tramelan(away) | 3-4 | 2. Liga Interregional - Group 2 |
| Oct 30, 2022 | Lausanne Sport II(home) | 0-5 | 2. Liga Interregional - Group 2 |
| Oct 22, 2022 | Spiez(away) | 0-2 | 2. Liga Interregional - Group 2 |
| Oct 15, 2022 | Courtételle(home) | 0-3 | 2. Liga Interregional - Group 2 |
| Oct 9, 2022 | La Tour / Le Pâquier(away) | 1-1 | 2. Liga Interregional - Group 2 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 5, 2022 | Romontois(home) | 6-0 | 2. Liga Interregional - Group 2 |
| Oct 29, 2022 | Besa Biel/Bienne(away) | 2-7 | 2. Liga Interregional - Group 2 |
| Oct 22, 2022 | Ajoie-Monterri(home) | 1-1 | 2. Liga Interregional - Group 2 |
| Oct 15, 2022 | Muri-Gümligen(away) | 1-3 | 2. Liga Interregional - Group 2 |
| Oct 8, 2022 | Châtel-St-Denis(home) | 2-1 | 2. Liga Interregional - Group 2 |
How many goals should we expect?
Matran score 0.9 and concede 2.7 goals per match over their last 12; Düdingen score 2.7 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Matran | 0.9 | 2.7 | 1 | 4/12 | 7/12 |
| Düdingen | 2.7 | 2.1 | 4 | 10/15 | 11/15 |
Over the last 12 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Düdingen | 30 | 15 | 8 | 7 | 52 | 40 | 53 |
A question about Matran vs Düdingen?
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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