Hillerød vs Vanløse: result 3-1 and analysis
Denmark Series - Group 1Regular Season - 16Kick-off on April 1, 2017 at 01:00 PM (UTC)Right to Dream Park, Farum
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What was the result of Hillerød vs Vanløse?
Hillerød won 3-1 on April 1, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Hillerød have 10 wins, 3 draws and 2 defeats; Vanløse have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 25, 2017 | Jægersborg(away) | 5-0 | Denmark Series - Group 1 |
| Nov 5, 2016 | Taastrup(home) | 3-0 | Denmark Series - Group 1 |
| Oct 29, 2016 | Kalundborg(home) | 4-1 | Denmark Series - Group 1 |
| Oct 22, 2016 | Stenløse(away) | 2-2 | Denmark Series - Group 1 |
| Oct 16, 2016 | Virum-Sorgenfri(home) | 3-0 | Denmark Series - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Mar 25, 2017 | Kalundborg(home) | 1-0 | Denmark Series - Group 1 |
| Nov 5, 2016 | Stenløse(away) | 3-1 | Denmark Series - Group 1 |
| Oct 29, 2016 | Virum-Sorgenfri(home) | 0-1 | Denmark Series - Group 1 |
| Oct 22, 2016 | KFUM Roskilde(away) | 1-2 | Denmark Series - Group 1 |
| Oct 15, 2016 | Kastrup(home) | 1-1 | Denmark Series - Group 1 |
What does the head-to-head say?
Across the last 3 meetings: 2 Hillerød wins, 0 draws, 1 Vanløse win.
| Date | Score | Competition |
|---|---|---|
| Sep 17, 2016 | Vanløse 1-2 Hillerød | Denmark Series - Group 1 |
| Jun 11, 2016 | Vanløse 1-0 Hillerød | Denmark Series - Group 1 |
| Oct 24, 2015 | Hillerød 2-0 Vanløse | Denmark Series - Group 1 |
How many goals should we expect?
Hillerød score 2.4 and concede 1.1 goals per match over their last 15; Vanløse score 1.7 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Hillerød | 2.4 | 1.1 | 5 | 9/15 | 12/15 |
| Vanløse | 1.7 | 1.3 | 3 | 9/15 | 8/15 |
Over the last 15 matches in all competitions.
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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