Grbalj vs Nikšić: prediction and stats
Second LeagueRegular Season - 30Kick-off on April 26, 2023 at 03:00 PM (UTC)Stadion Donja Sutvara, Radanovići
Match cancelled
What is the recent form of both teams?
Over their last 15 matches in all competitions, Grbalj have 5 wins, 3 draws and 7 defeats; Nikšić have 3, 5 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Apr 22, 2023 | Igalo(away) | 0-1 | Second League |
| Apr 16, 2023 | Berane(home) | 2-3 | Second League |
| Apr 12, 2023 | Mladost DG(home) | 0-1 | Second League |
| Apr 8, 2023 | Otrant-Olympic(away) | 0-3 | Second League |
| Apr 1, 2023 | Kom(home) | 2-0 | Second League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Dec 3, 2022 | Igalo(away) | 1-3 | Second League |
| Nov 27, 2022 | Berane(away) | 1-3 | Second League |
| Nov 20, 2022 | Mladost DG(home) | 0-0 | Second League |
| Nov 12, 2022 | Otrant-Olympic(away) | 2-0 | Second League |
| Nov 5, 2022 | Kom(home) | 1-3 | Second League |
What does the head-to-head say?
Across the last 2 meetings: 0 Grbalj wins, 1 draw, 1 Nikšić win.
| Date | Score | Competition |
|---|---|---|
| Oct 16, 2022 | Grbalj 1-1 Nikšić | Second League |
| Aug 28, 2022 | Nikšić 2-1 Grbalj | Second League |
How many goals should we expect?
Grbalj score 0.8 and concede 0.9 goals per match over their last 15; Nikšić score 0.8 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Grbalj | 0.8 | 0.9 | 6 | 4/15 | 4/15 |
| Nikšić | 0.8 | 1.6 | 5 | 6/15 | 5/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Grbalj | 10 | 4 | 4 | 2 | 13 | 9 | 16 |
A question about Grbalj vs Nikšić?
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