Velence SE vs Diosgyori VTK: result 0-3 and analysis
Magyar Kupa3rd RoundKick-off on October 30, 2012 at 11:30 AM (UTC)
Full time
What was the result of Velence SE vs Diosgyori VTK?
Diosgyori VTK won 0-3 on October 30, 2012.
Goalscorers
- 59′Jose Juan Luque JimenezDiosgyori VTK (pen.)
- 63′Tibor TiszaDiosgyori VTK
- 90′Tibor TiszaDiosgyori VTK
Official lineup for Velence SE vs Diosgyori VTK
The starting elevens fielded at kick-off.
Velence SE
- JJános Galaczi
- JJános Salacz
- BB. Kocsis
- AA. Odor
- LL. Bakos
- TT. Kadlecsik
- GGergő Totsche
- GGábor Fésű
- AAndrás Tóth
- SSzabolcs Somogyi
- JJános Puhnyák
Diosgyori VTK
- TTibor Tisza
- FFernando Miguel Fernandez Escribano
- PPaco Gallardo
- JJose Juan Luque Jimenez
- PPéter Takács
- MM. Csirszki
- II. Gal
- VViktor Vadász
- MMichal Hanek
- GG. Gohér
- NNorbert Tajti
What is the recent form of both teams?
Over their last 2 matches in all competitions, Velence SE have 1 win, 1 draw and 0 defeats; Diosgyori VTK have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 26, 2012 | Nagyatádi(home) | 2-1 | Magyar Kupa |
| Aug 11, 2012 | Maglódi TC(home) | 12-12 | Magyar Kupa |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2012 | Kaposvar(home) | 0-1 | NB I |
| Oct 21, 2012 | Debreceni VSC(away) | 0-2 | NB I |
| Oct 5, 2012 | MTK Budapest(home) | 2-1 | NB I |
| Sep 30, 2012 | Ferencvarosi TC(away) | 0-2 | NB I |
| Sep 26, 2012 | Orosháza(away) | 7-0 | Magyar Kupa |
How many goals should we expect?
Velence SE score 7.0 and concede 6.5 goals per match over their last 2; Diosgyori VTK score 1.3 and concede 1.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Velence SE | 7.0 | 6.5 | 0 | 2/2 | 2/2 |
| Diosgyori VTK | 1.3 | 1.1 | 5 | 6/15 | 8/15 |
Over the last 2 matches in all competitions.
A question about Velence SE vs Diosgyori VTK?
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
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