Match

Diosgyori VTK vs Paks: result 2-4 and analysis

NB IRegular Season - 9Kick-off on September 16, 2017 at 04:00 PM (UTC)Diósgyőri Stadion, Miskolc

Diosgyori VTK
2-4
Paks

Full time

What was the result of Diosgyori VTK vs Paks?

Paks won 2-4 on September 16, 2017.

Goalscorers

  • 7′R. UgraiDiosgyori VTK
  • 14′L. BarthaPaks
  • 39′L. BertusPaks
  • 50′N. IoannidisDiosgyori VTK
  • 72′B. DaruPaks
  • 90′D. KulcsárPaks

What is the recent form of both teams?

Over their last 15 matches in all competitions, Diosgyori VTK have 5 wins, 6 draws and 4 defeats; Paks have 3, 5 and 7.

The competition is shown for every match: in pre-season, several of these games are friendlies.

Diosgyori VTK
DateOpponentScoreCompetition
Sep 9, 2017Debreceni VSC(away)1-3NB I
Aug 26, 2017Mezokovesd-zsory(home)2-1NB I
Aug 19, 2017Ujpest(away)1-1NB I
Aug 12, 2017Puskas Academy(home)2-2NB I
Aug 5, 2017Balmazujvaros(away)0-4NB I
Paks
DateOpponentScoreCompetition
Sep 10, 2017Budapest Honved(home)2-2NB I
Sep 6, 2017Fehérvár FC(home)1-4NB I
Aug 26, 2017Vasas(away)1-3NB I
Aug 12, 2017Ferencvarosi TC(away)1-1NB I
Aug 5, 2017Szombathelyi Haladas(home)2-0NB I

What does the head-to-head say?

Across the last 6 meetings: 2 Diosgyori VTK wins, 2 draws, 2 Paks wins.

DateScoreCompetition
Apr 22, 2017Paks 0-1 Diosgyori VTKNB I
Nov 26, 2016Diosgyori VTK 2-0 PaksNB I
Aug 17, 2016Paks 2-1 Diosgyori VTKNB I
Apr 30, 2016Diosgyori VTK 0-2 PaksNB I
Nov 28, 2015Diosgyori VTK 1-1 PaksNB I
Aug 22, 2015Paks 1-1 Diosgyori VTKNB I

Last archived meeting: Paks vs Diosgyori VTK on Apr 22, 2017

How many goals should we expect?

Diosgyori VTK score 1.3 and concede 1.5 goals per match over their last 15; Paks score 1.4 and concede 1.7.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Diosgyori VTK1.31.549/159/15
Paks1.41.739/158/15

Over the last 15 matches in all competitions.

Where do both teams sit in the table?

2026-27 standings
#ClubPWDLGFGAPts
5Paks9423191714

A question about Diosgyori VTK vs Paks?

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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

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