Kozarmisleny FC vs Cigand SE: result 0-1 and analysis
NB IIRegular Season - 13Kick-off on October 16, 2016 at 12:30 PM (UTC)Kozármislenyi Stadion, Kozármisleny
Full time
What was the result of Kozarmisleny FC vs Cigand SE?
Cigand SE won 0-1 on October 16, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Kozarmisleny FC have 6 wins, 4 draws and 5 defeats; Cigand SE have 3, 3 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 2, 2016 | Cegledi VSE(away) | 2-2 | NB II |
| Sep 25, 2016 | Szeol Sc(home) | 1-0 | NB II |
| Sep 21, 2016 | Veszprém(away) | 3-0 | Magyar Kupa |
| Sep 18, 2016 | Szeged 2011(away) | 0-0 | NB II |
| Sep 15, 2016 | Bekescsaba 1912(home) | 0-2 | NB II |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 2, 2016 | Szeol Sc(home) | 3-0 | NB II |
| Sep 25, 2016 | Bekescsaba 1912(away) | 0-1 | NB II |
| Sep 21, 2016 | Baktalórántháza(away) | 7-7 | Magyar Kupa |
| Sep 18, 2016 | Soproni VSE(home) | 0-1 | NB II |
| Sep 14, 2016 | Kisvarda FC(away) | 0-3 | NB II |
How many goals should we expect?
Kozarmisleny FC score 1.3 and concede 1.1 goals per match over their last 15; Cigand SE score 1.3 and concede 2.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Kozarmisleny FC | 1.3 | 1.1 | 6 | 6/15 | 7/15 |
| Cigand SE | 1.3 | 2.2 | 2 | 6/15 | 9/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Kozarmisleny FC | 9 | 1 | 1 | 7 | 6 | 18 | 4 |
A question about Kozarmisleny FC vs Cigand SE?
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