Debreceni VSC vs Puskas Academy: result 2-1 and analysis
NB IRegular Season - 14Kick-off on November 9, 2013 at 01:00 PM (UTC)Nagyerdei Stadion, Debrecen
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What was the result of Debreceni VSC vs Puskas Academy?
Debreceni VSC won 2-1 on November 9, 2013.
Goalscorers
- 10′Péter SzakályDebreceni VSC
- 24′P. TischlerPuskas Academy
- 28′Dalibor VolasDebreceni VSC (pen.)
What is the recent form of both teams?
Over their last 15 matches in all competitions, Debreceni VSC have 9 wins, 3 draws and 3 defeats; Puskas Academy 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 |
|---|---|---|---|
| Nov 3, 2013 | Ujpest(away) | 4-1 | NB I |
| Oct 30, 2013 | ESMTK(away) | 2-1 | Magyar Kupa |
| Oct 26, 2013 | Pápa(home) | 2-2 | NB I |
| Oct 19, 2013 | Kecskeméti TE(away) | 3-0 | NB I |
| Oct 4, 2013 | Paks(home) | 2-2 | NB I |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Nov 2, 2013 | MTK Budapest(home) | 1-1 | NB I |
| Oct 27, 2013 | Gyori ETO FC(away) | 2-2 | NB I |
| Oct 22, 2013 | Kecskeméti TE(home) | 0-0 | Magyar Kupa |
| Oct 19, 2013 | Fehérvár FC(away) | 0-3 | NB I |
| Oct 5, 2013 | Pécsi MFC(away) | 2-1 | NB I |
How many goals should we expect?
Debreceni VSC score 2.3 and concede 1.2 goals per match over their last 15; Puskas Academy score 1.3 and concede 1.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Debreceni VSC | 2.3 | 1.2 | 4 | 10/15 | 12/15 |
| Puskas Academy | 1.3 | 1.9 | 2 | 10/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Debreceni VSC sit 9th in NB I (5 points from 5 matches) and Puskas Academy sit 1st (12 points from 5 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Puskas Academy | 5 | 4 | 0 | 1 | 9 | 6 | 12 |
| 9 | Debreceni VSC | 5 | 1 | 2 | 2 | 4 | 7 | 5 |
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