Hidasnémeti vs Salgótarjáni BTC: result 0-2 and analysis
NB III - NortheastKeleti - 16Kick-off on November 7, 2021 at 12:00 PM (UTC)
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What was the result of Hidasnémeti vs Salgótarjáni BTC?
Salgótarjáni BTC won 0-2 on November 7, 2021.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Hidasnémeti have 2 wins, 1 draw and 12 defeats; Salgótarjáni BTC have 0, 6 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 31, 2021 | Sényő Carnifex(away) | 0-3 | NB III - Northeast |
| Oct 24, 2021 | Tállya(home) | 0-1 | NB III - Northeast |
| Oct 20, 2021 | Újpest II(away) | 0-2 | NB III - Northeast |
| Oct 17, 2021 | Debrecen II(home) | 1-4 | NB III - Northeast |
| Oct 10, 2021 | Tiszafuredi VSE(away) | 1-5 | NB III - Northeast |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 31, 2021 | Törökszentmiklós(home) | 1-1 | NB III - Northeast |
| Oct 27, 2021 | Füzesgyarmati(away) | 3-3 | NB III - Northeast |
| Oct 24, 2021 | Diósgyőr II(away) | 1-2 | NB III - Northeast |
| Oct 17, 2021 | Sényő Carnifex(home) | 0-0 | NB III - Northeast |
| Oct 10, 2021 | Tállya(away) | 1-2 | NB III - Northeast |
How many goals should we expect?
Hidasnémeti score 0.8 and concede 3.6 goals per match over their last 15; Salgótarjáni BTC score 0.7 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Hidasnémeti | 0.8 | 3.6 | 0 | 6/15 | 12/15 |
| Salgótarjáni BTC | 0.7 | 2.1 | 3 | 8/15 | 10/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 13 | Salgótarjáni BTC | 14 | 4 | 1 | 9 | 11 | 22 | 13 |
A question about Hidasnémeti vs Salgótarjáni BTC?
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