BFA vs Minija: result 5-4 and analysis
1 LygaRegular Season - 11Kick-off on June 9, 2019 at 01:00 PM (UTC)BFA Maniežas, Vilnius
Full time
What was the result of BFA vs Minija?
BFA won 5-4 on June 9, 2019.
Goalscorers
- 14′?Minija
- 29′?BFA
- 31′?BFA
- 55′?Minija
- 56′?Minija
- 60′?Minija
- 74′?BFA
- 82′?BFA (pen.)
- 90′?BFA
What is the recent form of both teams?
Over their last 9 matches in all competitions, BFA have 2 wins, 1 draw and 6 defeats; Minija have 3, 2 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 1, 2019 | Banga(away) | 1-2 | 1 Lyga |
| May 19, 2019 | Vilniaus Vytis(home) | 0-0 | 1 Lyga |
| May 15, 2019 | Kupiškis(away) | 1-3 | 1 Lyga |
| May 12, 2019 | Trakai II(home) | 2-1 | 1 Lyga |
| May 8, 2019 | Džiugas Telšiai(away) | 2-3 | 1 Lyga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 1, 2019 | Šiauliai(home) | 0-3 | 1 Lyga |
| May 28, 2019 | Trakai II(home) | 2-1 | 1 Lyga |
| May 20, 2019 | Dainava(away) | 1-0 | 1 Lyga |
| May 15, 2019 | Banga(home) | 1-2 | 1 Lyga |
| May 11, 2019 | Jonava(home) | 0-2 | 1 Lyga |
How many goals should we expect?
BFA score 1.0 and concede 1.9 goals per match over their last 9; Minija score 0.9 and concede 3.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| BFA | 1.0 | 1.9 | 1 | 6/9 | 6/9 |
| Minija | 0.9 | 3.3 | 2 | 8/15 | 10/15 |
Over the last 9 matches in all competitions.
Where do both teams sit in the table?
BFA sit 7th in 1 Lyga (43 points from 26 matches) and Minija sit 1st (67 points from 25 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | Minija | 25 | 22 | 1 | 2 | 68 | 13 | 67 |
| 7 | BFA | 26 | 13 | 4 | 9 | 40 | 37 | 43 |
A question about BFA vs Minija?
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