Tindastóll vs KFG: result 3-0 and analysis
2. DeildRegular Season - 16Kick-off on August 17, 2019 at 03:00 PM (UTC)Sauðárkróksvöllur, Sauðárkrókur
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What was the result of Tindastóll vs KFG?
Tindastóll won 3-0 on August 17, 2019.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Tindastóll have 1 win, 3 draws and 11 defeats; KFG have 5, 0 and 10.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 8, 2019 | Dalvík / Reynir(away) | 2-3 | 2. Deild |
| Jul 31, 2019 | Vídir(home) | 0-3 | 2. Deild |
| Jul 27, 2019 | Fjardabyggd(home) | 2-2 | 2. Deild |
| Jul 20, 2019 | IR Reykjavik(away) | 0-2 | 2. Deild |
| Jul 13, 2019 | Vestri(home) | 2-1 | 2. Deild |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 10, 2019 | Leiknir F.(home) | 2-3 | 2. Deild |
| Jul 31, 2019 | Thróttur Vogar(away) | 0-5 | 2. Deild |
| Jul 25, 2019 | Vídir(home) | 3-1 | 2. Deild |
| Jul 19, 2019 | Dalvík / Reynir(away) | 1-2 | 2. Deild |
| Jul 12, 2019 | IR Reykjavik(home) | 2-3 | 2. Deild |
What does the head-to-head say?
In the last meeting: 0 Tindastóll wins, 0 draws, 1 KFG win.
| Date | Score | Competition |
|---|---|---|
| Jun 1, 2019 | KFG 4-2 Tindastóll | 2. Deild |
How many goals should we expect?
Tindastóll score 0.9 and concede 2.5 goals per match over their last 15; KFG score 1.7 and concede 2.4.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Tindastóll | 0.9 | 2.5 | 1 | 8/15 | 12/15 |
| KFG | 1.7 | 2.4 | 2 | 9/15 | 13/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 11 | KFG | 22 | 7 | 1 | 14 | 38 | 58 | 22 |
A question about Tindastóll vs KFG?
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