BFA vs Kupiškis: result 0-2 and analysis
1 LygaRegular Season - 23Kick-off on October 23, 2019 at 03:30 PM (UTC)BFA Maniežas, Vilnius
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What was the result of BFA vs Kupiškis?
Kupiškis won 0-2 on October 23, 2019.
Goalscorers
- 44′?Kupiškis
- 88′?Kupiškis
What is the recent form of both teams?
Over their last 15 matches in all competitions, BFA have 5 wins, 2 draws and 8 defeats; Kupiškis have 5, 2 and 8.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 20, 2019 | Šiauliai(away) | 2-5 | 1 Lyga |
| Oct 16, 2019 | Žalgiris II(away) | 1-1 | 1 Lyga |
| Oct 6, 2019 | Atmosfera(home) | 3-0 | 1 Lyga |
| Sep 27, 2019 | Minija(away) | 0-2 | 1 Lyga |
| Sep 22, 2019 | Banga(home) | 2-2 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 19, 2019 | Banga(away) | 1-5 | 1 Lyga |
| Oct 13, 2019 | Dainava(away) | 1-3 | 1 Lyga |
| Oct 5, 2019 | Minija(home) | 1-4 | 1 Lyga |
| Sep 28, 2019 | Hegelmann Litauen(home) | 0-0 | 1 Lyga |
| Sep 22, 2019 | Trakai II(home) | 1-7 | 1 Lyga |
What does the head-to-head say?
In the last meeting: 0 BFA wins, 0 draws, 1 Kupiškis win.
| Date | Score | Competition |
|---|---|---|
| May 15, 2019 | Kupiškis 3-1 BFA | 1 Lyga |
How many goals should we expect?
BFA score 1.7 and concede 1.9 goals per match over their last 15; Kupiškis score 1.7 and concede 2.1.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| BFA | 1.7 | 1.9 | 3 | 8/15 | 10/15 |
| Kupiškis | 1.7 | 2.1 | 4 | 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 |
|---|---|---|---|---|---|---|---|---|
| 7 | BFA | 26 | 13 | 4 | 9 | 40 | 37 | 43 |
A question about BFA vs Kupiškis?
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