Skála II vs B71: result 1-1 and analysis
1. DeildRegular Season - 13Kick-off on June 13, 2019 at 06:30 PM (UTC)Undir Mýruhjalla, Skáli, Eysturoy
Full time
What was the result of Skála II vs B71?
Skála II and B71 drew 1-1 on June 13, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Skála II have 3 wins, 9 draws and 3 defeats; B71 have 5, 3 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 1, 2019 | KÍ II(home) | 2-3 | 1. Deild |
| May 25, 2019 | HB II(away) | 1-4 | 1. Deild |
| May 18, 2019 | B68(home) | 1-1 | 1. Deild |
| May 11, 2019 | Víkingur II(away) | 2-2 | 1. Deild |
| May 4, 2019 | HB II(home) | 1-1 | 1. Deild |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Jun 1, 2019 | EB / Streymur II(home) | 2-1 | 1. Deild |
| May 25, 2019 | B36 II(away) | 3-3 | 1. Deild |
| May 11, 2019 | NSÍ II(away) | 0-4 | 1. Deild |
| May 4, 2019 | B36 II(home) | 2-2 | 1. Deild |
| Apr 27, 2019 | B68(home) | 4-1 | 1. Deild |
What does the head-to-head say?
Across the last 4 meetings: 0 Skála II wins, 2 draws, 2 B71 wins.
| Date | Score | Competition |
|---|---|---|
| Mar 9, 2019 | B71 0-0 Skála II | 1. Deild |
| Sep 2, 2018 | B71 0-0 Skála II | 1. Deild |
| Jun 2, 2018 | Skála II 3-4 B71 | 1. Deild |
| May 5, 2018 | B71 1-0 Skála II | 1. Deild |
How many goals should we expect?
Skála II score 1.7 and concede 1.6 goals per match over their last 15; B71 score 1.6 and concede 2.5.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Skála II | 1.7 | 1.6 | 2 | 13/15 | 9/15 |
| B71 | 1.6 | 2.5 | 3 | 9/15 | 12/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | B71 | 25 | 19 | 3 | 3 | 78 | 27 | 60 |
A question about Skála II vs B71?
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