B 93 vs HIK: result 4-2 and analysis
2. DivisionRegular Season - 10Kick-off on October 8, 2016 at 01:00 PM (UTC)Sundby Idrætspark, København
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What was the result of B 93 vs HIK?
B 93 won 4-2 on October 8, 2016.
What is the recent form of both teams?
Over their last 15 matches in all competitions, B 93 have 6 wins, 3 draws and 6 defeats; HIK have 7, 2 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 5, 2016 | Fredensborg BI(home) | 0-2 | 2. Division |
| Sep 30, 2016 | Hvidovre(away) | 1-0 | 2. Division |
| Sep 24, 2016 | Frem(home) | 1-1 | 2. Division |
| Sep 10, 2016 | HIK(away) | 2-0 | 2. Division |
| Sep 4, 2016 | Avarta(away) | 1-0 | 2. Division |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 1, 2016 | Holbæk B&I(home) | 3-1 | 2. Division |
| Sep 23, 2016 | Avarta(home) | 2-3 | 2. Division |
| Sep 17, 2016 | Brønshøj(away) | 2-1 | 2. Division |
| Sep 10, 2016 | B 93(home) | 0-2 | 2. Division |
| Sep 4, 2016 | Hvidovre(away) | 1-2 | 2. Division |
What does the head-to-head say?
In the last meeting: 1 B 93 win, 0 draws, 0 HIK wins.
| Date | Score | Competition |
|---|---|---|
| Sep 10, 2016 | HIK 0-2 B 93 | 2. Division |
How many goals should we expect?
B 93 score 1.5 and concede 1.3 goals per match over their last 15; HIK score 1.7 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| B 93 | 1.5 | 1.3 | 4 | 8/15 | 7/15 |
| HIK | 1.7 | 1.6 | 3 | 9/15 | 11/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
B 93 sit 3rd in 2. Division (18 points from 11 matches) and HIK sit 10th (9 points from 11 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 3 | B 93 | 11 | 5 | 3 | 3 | 19 | 14 | 18 |
| 10 | HIK | 11 | 2 | 3 | 6 | 9 | 19 | 9 |
A question about B 93 vs HIK?
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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