Sasa vs Rosoman: result 3-0 and analysis
Second LeagueEast - 27Kick-off on May 15, 2021 at 02:00 PM (UTC)Gradski stadion, Makedonska Kamenica
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What was the result of Sasa vs Rosoman?
Sasa won 3-0 on May 15, 2021.
What is the recent form of both teams?
Over their last 15 matches in all competitions, Sasa have 5 wins, 6 draws and 4 defeats; Rosoman have 0, 1 and 14.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 8, 2021 | Tikveš(away) | 1-3 | Second League |
| May 1, 2021 | Plačkovica(home) | 1-2 | Second League |
| Apr 24, 2021 | Pehchevo(away) | 1-1 | Second League |
| Apr 17, 2021 | Pobeda(home) | 2-1 | Second League |
| Apr 10, 2021 | Kozuv Gevgelija(away) | 0-1 | Second League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| May 8, 2021 | Plačkovica(home) | 0-1 | Second League |
| May 1, 2021 | Pobeda(away) | 1-3 | Second League |
| Apr 24, 2021 | Sloga Vinica(home) | 1-2 | Second League |
| Apr 17, 2021 | Bregalnica Štip(away) | 1-5 | Second League |
| Apr 10, 2021 | Tikveš(home) | 1-1 | Second League |
What does the head-to-head say?
Across the last 2 meetings: 1 Sasa win, 0 draws, 1 Rosoman win.
| Date | Score | Competition |
|---|---|---|
| Nov 25, 2020 | Sasa 5-0 Rosoman | Second League |
| Sep 19, 2020 | Rosoman 3-2 Sasa | Second League |
How many goals should we expect?
Sasa score 1.5 and concede 1.1 goals per match over their last 15; Rosoman score 0.7 and concede 3.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sasa | 1.5 | 1.1 | 4 | 10/15 | 7/15 |
| Rosoman | 0.7 | 3.3 | 0 | 10/15 | 12/15 |
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 | Sasa | 30 | 9 | 9 | 12 | 47 | 53 | 36 |
A question about Sasa vs Rosoman?
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