Cegledi VSE vs Kisvárda II: result 2-3 and analysis
NB III - NortheastKeleti - 9Kick-off on September 9, 2020 at 02:30 PM (UTC)Malomtó széli sporttelep, Cegléd
Full time
What was the result of Cegledi VSE vs Kisvárda II?
Kisvárda II won 2-3 on September 9, 2020.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Cegledi VSE have 8 wins, 2 draws and 5 defeats; Kisvárda II have 3, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 5, 2020 | Sajóbábony Vegyész(away) | 1-0 | NB III - Northeast |
| Aug 30, 2020 | Tiszaújváros(home) | 1-2 | NB III - Northeast |
| Aug 26, 2020 | Debrecen II(away) | 1-3 | NB III - Northeast |
| Aug 23, 2020 | Diósgyőr II(home) | 1-5 | NB III - Northeast |
| Aug 16, 2020 | Jászberényi Vasas(away) | 0-1 | NB III - Northeast |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 5, 2020 | Eger(home) | 0-0 | NB III - Northeast |
| Aug 30, 2020 | Sajóbábony Vegyész(home) | 2-2 | NB III - Northeast |
| Aug 26, 2020 | Tiszaújváros(away) | 0-0 | NB III - Northeast |
| Aug 23, 2020 | Debrecen II(home) | 1-3 | NB III - Northeast |
| Aug 16, 2020 | Diósgyőr II(away) | 4-3 | NB III - Northeast |
How many goals should we expect?
Cegledi VSE score 1.6 and concede 1.2 goals per match over their last 15; Kisvárda II score 1.6 and concede 1.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Cegledi VSE | 1.6 | 1.2 | 5 | 8/15 | 8/15 |
| Kisvárda II | 1.6 | 1.7 | 2 | 6/9 | 6/9 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Kisvárda II | 12 | 5 | 6 | 1 | 20 | 13 | 21 |
A question about Cegledi VSE vs Kisvárda II?
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