Dekani vs Radomlje: result 1-3 and analysis
2. SNLRegular Season - 7Kick-off on September 7, 2019 at 02:30 PM (UTC)Igrišče Ivan Gregorič, Dekani
Full time
What was the result of Dekani vs Radomlje?
Radomlje won 1-3 on September 7, 2019.
Goalscorers
- 12′Anže PišekRadomlje
- 28′Stefano BorghiDekani
- 61′Anže PišekRadomlje
- 89′Lan GojakRadomlje
What is the recent form of both teams?
Over their last 15 matches in all competitions, Dekani have 4 wins, 4 draws and 7 defeats; Radomlje have 12, 2 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 31, 2019 | Fužinar(away) | 1-4 | 2. SNL |
| Aug 24, 2019 | Rogaška(home) | 3-1 | 2. SNL |
| Aug 17, 2019 | Krško(away) | 0-3 | 2. SNL |
| Aug 10, 2019 | Bilje(home) | 1-2 | 2. SNL |
| Aug 3, 2019 | Dob(away) | 3-3 | 2. SNL |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 1, 2019 | Dravograd(home) | 6-1 | 2. SNL |
| Aug 24, 2019 | Fužinar(away) | 2-0 | 2. SNL |
| Aug 17, 2019 | Beltinci(home) | 4-0 | 2. SNL |
| Aug 14, 2019 | Dobrovce(away) | 10-0 | Cup |
| Aug 10, 2019 | Rogaška(away) | 2-0 | 2. SNL |
What does the head-to-head say?
Across the last 2 meetings: 0 Dekani win(s), 1 draw(s), 1 Radomlje win(s).
| Date | Score | Competition |
|---|---|---|
| Mar 23, 2019 | Dekani 2-2 Radomlje | 2. SNL |
| Sep 5, 2018 | Radomlje 5-1 Dekani | 2. SNL |
How many goals should we expect?
Dekani score 1.5 and concede 2.2 goals per match over their last 15; Radomlje score 3.2 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Dekani | 1.5 | 2.2 | 3 | 9/15 | 12/15 |
| Radomlje | 3.2 | 1.1 | 7 | 8/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Dekani | 3 | 1 | 0 | 2 | 3 | 3 | 3 |
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy