Match

Diosgyori VTK vs VAC: result 2-0 and analysis

Magyar Kupa8th FinalsKick-off on February 20, 2018 at 05:00 PM (UTC)Városi Stadion, Mezőkövesd

Diosgyori VTK
2-0
VAC

Full time

What was the result of Diosgyori VTK vs VAC?

Diosgyori VTK won 2-0 on February 20, 2018.

Goalscorers

  • 30′N. IoannidisDiosgyori VTK
  • 87′P. BacsaDiosgyori VTK

Official lineup for Diosgyori VTK vs VAC

The starting elevens fielded at kick-off.

Diosgyori VTK

  1. FF. Hasani
  2. PP. Bacsa
  3. NN. Ioannidis
  1. DDiego Vela
  2. SS. Shestakov
  3. BB. Tóth
  1. ZZoltán Lipták
  2. DDejan Karan
  3. DD. Brković
  4. MM. Tamás
  1. BB. Antal

VAC

  1. ÁÁ. Balajti
  2. RR. Zsolnai
  1. ZZoltan Burany
  2. DD. Kákonyi
  3. GG. Tóth
  1. CC. Hegedűs
  2. MM. Gulyas
  3. DD. Görgényi
  4. FFerenc Tóth
  5. NNormann Szabó
  1. AAttila Abu
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What is the recent form of both teams?

Over their last 15 matches in all competitions, Diosgyori VTK have 7 wins, 1 draw and 7 defeats; VAC have 10, 2 and 3.

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

Diosgyori VTK
DateOpponentScoreCompetition
Dec 9, 2017Debreceni VSC(home)3-2NB I
Dec 2, 2017Mezokovesd-zsory(away)0-0NB I
Nov 29, 2017Soroksar(away)3-1Magyar Kupa
Nov 25, 2017Ujpest(home)1-2NB I
Nov 18, 2017Puskas Academy(away)0-1NB I
VAC
DateOpponentScoreCompetition
Dec 10, 2017Kazincbarcikai(home)1-0NB II
Dec 3, 2017Soroksar(away)1-2NB II
Nov 29, 2017Fehérvár FC(home)3-1Magyar Kupa
Nov 26, 2017Dorogi FC(away)0-2NB II
Nov 19, 2017Nyiregyhaza(home)1-1NB II

How many goals should we expect?

Diosgyori VTK score 1.8 and concede 1.4 goals per match over their last 15; VAC score 1.9 and concede 0.8.

ClubGoals scored / matchGoals conceded / matchClean sheetsBoth teams scoredOver 2.5 goals
Diosgyori VTK1.81.458/1511/15
VAC1.90.858/156/15

Over the last 15 matches in all competitions.

A question about Diosgyori VTK vs VAC?

Ask Footlab AI: lineups, absences, player form, stats, how the match could unfold.

Sign-in required. No odds displayed, no affiliation: the method is published and the accuracy is measured.

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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