Rudar Kakanj vs Gradina: result 1-0 and analysis
1st League - FBiHFBiH - 12Kick-off on October 30, 2021 at 12:30 PM (UTC)Stadion Pod Vardom, Kakanj
Full time
What was the result of Rudar Kakanj vs Gradina?
Rudar Kakanj won 1-0 on October 30, 2021.
Goalscorers
- 33′V. KulovićRudar Kakanj (pen.)
What is the recent form of both teams?
Over their last 15 matches in all competitions, Rudar Kakanj have 6 wins, 4 draws and 5 defeats; Gradina have 6, 0 and 6.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 24, 2021 | TOŠK Tešanj(away) | 0-1 | 1st League - FBiH |
| Oct 16, 2021 | Radnik Hadžići(home) | 0-2 | 1st League - FBiH |
| Oct 10, 2021 | Tomislav(away) | 0-0 | 1st League - FBiH |
| Oct 2, 2021 | Jedinstvo Bihać(home) | 1-0 | 1st League - FBiH |
| Sep 25, 2021 | Orašje(away) | 1-2 | 1st League - FBiH |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 23, 2021 | Vis Kosova(home) | 1-0 | 1st League - FBiH |
| Oct 16, 2021 | Budućnost Banovići(away) | 2-3 | 1st League - FBiH |
| Oct 10, 2021 | Bratstvo Gračanica(home) | 2-1 | 1st League - FBiH |
| Oct 3, 2021 | GOŠK Gabela(away) | 1-6 | 1st League - FBiH |
| Sep 28, 2021 | Tuzla City(home) | 2-4 | Cup |
How many goals should we expect?
Rudar Kakanj score 0.9 and concede 1.3 goals per match over their last 15; Gradina score 2.1 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Rudar Kakanj | 0.9 | 1.3 | 5 | 6/15 | 6/15 |
| Gradina | 2.1 | 2.3 | 2 | 8/12 | 9/12 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 16 | Rudar Kakanj | 12 | 2 | 2 | 8 | 7 | 25 | 8 |
A question about Rudar Kakanj vs Gradina?
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