Panevėžys II vs Be1 NFA: result 0-2 and analysis
1 LygaRegular Season - 29Kick-off on November 7, 2022 at 03:00 PM (UTC)Žemynos progimnazijos stadionas, Panevėžys
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What was the result of Panevėžys II vs Be1 NFA?
Be1 NFA won 0-2 on November 7, 2022.
Goalscorers
- 12′?Be1 NFA
- 90′?Be1 NFA
What is the recent form of both teams?
Over their last 15 matches in all competitions, Panevėžys II have 9 wins, 1 draws and 5 defeats; Be1 NFA have 7, 5 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 28, 2022 | Garliava(away) | 2-0 | 1 Lyga |
| Oct 22, 2022 | Dainava(home) | 1-3 | 1 Lyga |
| Oct 14, 2022 | Nevėžis(away) | 2-1 | 1 Lyga |
| Oct 8, 2022 | Šilas(home) | 3-0 | 1 Lyga |
| Oct 3, 2022 | FA Šiauliai II(away) | 1-3 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 29, 2022 | Žalgiris II(home) | 1-0 | 1 Lyga |
| Oct 23, 2022 | Banga II(away) | 0-0 | 1 Lyga |
| Oct 15, 2022 | Atmosfera(home) | 2-0 | 1 Lyga |
| Oct 12, 2022 | Neptūną Klaipėda(away) | 1-2 | 1 Lyga |
| Oct 8, 2022 | Babrungas(away) | 1-0 | 1 Lyga |
What does the head-to-head say?
Across the last 1 meetings: 0 Panevėžys II win(s), 0 draw(s), 1 Be1 NFA win(s).
| Date | Score | Competition |
|---|---|---|
| Jul 3, 2022 | Be1 NFA 2-1 Panevėžys II | 1 Lyga |
Last archived meeting: Be1 NFA vs Panevėžys II on Jul 3, 2022
How many goals should we expect?
Panevėžys II score 2.0 and concede 1.5 goals per match over their last 15; Be1 NFA score 1.2 and concede 0.7.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Panevėžys II | 2.0 | 1.5 | 2 | 13/15 | 13/15 |
| Be1 NFA | 1.2 | 0.7 | 6 | 8/15 | 4/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Be1 NFA | 20 | 12 | 2 | 6 | 33 | 24 | 38 |
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy