Puskas Academy vs Ujpest: result 1-2 and analysis
NB IRegular Season - 2Kick-off on August 3, 2013 at 07:00 PM (UTC)Puskás Akadémia Pancho Aréna, Felcsút
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What was the result of Puskas Academy vs Ujpest?
Ujpest won 1-2 on August 3, 2013.
Goalscorers
- 17′P. TischlerPuskas Academy
- 23′P. KabatUjpest
- 61′Jarmo AhjuperaUjpest
What is the recent form of both teams?
Over their last 15 matches in all competitions, Puskas Academy have 8 wins, 5 draws and 2 defeats; Ujpest have 6, 2 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 26, 2013 | Pápa(away) | 1-1 | NB I |
| Jun 1, 2013 | Soproni VSE(home) | 1-0 | NB II |
| May 24, 2013 | Tatabánya(home) | 0-1 | NB II |
| May 19, 2013 | BKV Előre(away) | 1-2 | NB II |
| May 11, 2013 | Kaposvári Rákóczi FC II(home) | 2-0 | NB II |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jul 27, 2013 | Paks(home) | 1-2 | NB I |
| Jun 2, 2013 | Siofok(away) | 1-0 | NB I |
| May 24, 2013 | Szombathelyi Haladas(home) | 0-1 | NB I |
| May 18, 2013 | Eger(away) | 2-1 | NB I |
| May 11, 2013 | Budapest Honved(home) | 2-4 | NB I |
How many goals should we expect?
Puskas Academy score 1.3 and concede 0.6 goals per match over their last 15; Ujpest score 1.1 and concede 1.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Puskas Academy | 1.3 | 0.6 | 8 | 6/15 | 3/15 |
| Ujpest | 1.1 | 1.5 | 4 | 8/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
Puskas Academy sit 1st in NB I (18 points from 9 matches) and Ujpest sit 4th (15 points from 9 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Puskas Academy | 9 | 6 | 0 | 3 | 14 | 10 | 18 |
| 4 | Ujpest | 9 | 4 | 3 | 2 | 18 | 14 | 15 |
A question about Puskas Academy vs Ujpest?
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