Šilas vs Be1 NFA: prediction and stats
1 LygaRegular Season - 24Kick-off on September 30, 2023 at 12:00 PM (UTC)Prienų stadionas, Prienai
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Šilas have 4 wins, 2 draws and 9 defeats; Be1 NFA have 8, 1 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 25, 2023 | Kauno Žalgiris II(away) | 0-3 | 1 Lyga |
| Sep 15, 2023 | Babrungas(away) | 2-6 | 1 Lyga |
| Sep 6, 2023 | Trakai II(home) | 0-4 | 1 Lyga |
| Aug 30, 2023 | BFA(home) | 0-0 | 1 Lyga |
| Aug 26, 2023 | Ekranas(away) | 1-0 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 23, 2023 | Babrungas(home) | 2-0 | 1 Lyga |
| Sep 16, 2023 | BFA(away) | 1-0 | 1 Lyga |
| Sep 1, 2023 | Ekranas(home) | 1-0 | 1 Lyga |
| Aug 28, 2023 | Žalgiris II(away) | 1-0 | 1 Lyga |
| Aug 20, 2023 | Panevėžys II(home) | 3-1 | 1 Lyga |
What does the head-to-head say?
Across the last 3 meetings: 1 Šilas win, 2 draws, 0 Be1 NFA wins.
| Date | Score | Competition |
|---|---|---|
| May 13, 2023 | Be1 NFA 1-2 Šilas | 1 Lyga |
| Nov 12, 2022 | Be1 NFA 1-1 Šilas | 1 Lyga |
| Jul 6, 2022 | Šilas 1-1 Be1 NFA | 1 Lyga |
How many goals should we expect?
Šilas score 0.8 and concede 2.5 goals per match over their last 15; Be1 NFA score 1.5 and concede 1.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Šilas | 0.8 | 2.5 | 6 | 5/15 | 9/15 |
| Be1 NFA | 1.5 | 1.3 | 5 | 7/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | Be1 NFA | 25 | 16 | 3 | 6 | 45 | 27 | 51 |
A question about Šilas vs Be1 NFA?
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