Sloga vs Čapljina: result 2-1 and analysis
1st League - FBiHRegular Season - 13Kick-off on October 29, 2017 at 12:30 PM (UTC)
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What was the result of Sloga vs Čapljina?
Sloga won 2-1 on October 29, 2017.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sloga have 9 wins, 1 draws and 5 defeats; Čapljina have 9, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 21, 2017 | Velež(away) | 0-3 | 1st League - FBiH |
| Oct 15, 2017 | Rudar Kakanj(home) | 3-0 | 1st League - FBiH |
| Oct 8, 2017 | Iskra(away) | 0-0 | 1st League - FBiH |
| Oct 1, 2017 | Bosna Visoko(home) | 6-1 | 1st League - FBiH |
| Sep 23, 2017 | Travnik(away) | 2-0 | 1st League - FBiH |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 20, 2017 | Igman Konjic(home) | 0-0 | 1st League - FBiH |
| Oct 14, 2017 | Slaven Živinice(home) | 3-1 | 1st League - FBiH |
| Oct 8, 2017 | Orašje(away) | 0-5 | 1st League - FBiH |
| Sep 30, 2017 | Rudar Kakanj(home) | 2-1 | 1st League - FBiH |
| Sep 23, 2017 | Iskra(away) | 2-1 | 1st League - FBiH |
What does the head-to-head say?
Across the last 2 meetings: 1 Sloga win(s), 0 draw(s), 1 Čapljina win(s).
| Date | Score | Competition |
|---|---|---|
| May 27, 2017 | Čapljina 1-0 Sloga | 1st League - FBiH |
| Nov 6, 2016 | Sloga 3-2 Čapljina | 1st League - FBiH |
How many goals should we expect?
Sloga score 1.8 and concede 0.9 goals per match over their last 15; Čapljina score 1.4 and concede 1.2.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sloga | 1.8 | 0.9 | 9 | 2/15 | 5/15 |
| Čapljina | 1.4 | 1.2 | 6 | 7/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 8 | Čapljina | 1 | 0 | 1 | 0 | 2 | 2 | 1 |
How does Footlab 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. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy