Tårnby FF vs KFUM Roskilde: result 0-1 and analysis
Denmark Series - Group 1Group 1 - 6Kick-off on September 6, 2019 at 04:00 PM (UTC)Vestamager Idrætsanlæg, Kastrup
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What was the result of Tårnby FF vs KFUM Roskilde?
KFUM Roskilde won 0-1 on September 6, 2019.
What is the recent form of both teams?
Over their last 11 matches in all competitions, Tårnby FF have 3 wins, 0 draws and 8 defeats; KFUM Roskilde have 9, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 31, 2019 | LSF(away) | 0-3 | Denmark Series - Group 1 |
| Aug 23, 2019 | Herlev(home) | 1-0 | Denmark Series - Group 1 |
| Aug 17, 2019 | Fremad Valby(away) | 0-2 | Denmark Series - Group 1 |
| Aug 9, 2019 | Skjold Birkerød(home) | 2-4 | Denmark Series - Group 1 |
| Aug 3, 2019 | Køge Nord(away) | 0-2 | Denmark Series - Group 1 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 3, 2019 | HB Koge(home) | 1-3 | DBU Pokalen |
| Aug 31, 2019 | BSF(home) | 1-1 | Denmark Series - Group 1 |
| Aug 24, 2019 | Allerød(home) | 5-4 | Denmark Series - Group 1 |
| Aug 17, 2019 | LSF(away) | 0-2 | Denmark Series - Group 1 |
| Aug 10, 2019 | Herlev(home) | 2-0 | Denmark Series - Group 1 |
How many goals should we expect?
Tårnby FF score 1.2 and concede 2.5 goals per match over their last 11; KFUM Roskilde score 2.9 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tårnby FF | 1.2 | 2.5 | 1 | 7/11 | 8/11 |
| KFUM Roskilde | 2.9 | 1.3 | 6 | 7/15 | 10/15 |
Over the last 11 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Tårnby FF | 18 | 8 | 6 | 4 | 28 | 25 | 30 |
A question about Tårnby FF vs KFUM Roskilde?
Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.
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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