Sinđelić vs Vlasina: result 2-1 and analysis
Srpska Liga - EastEast - 11Kick-off on October 26, 2019 at 12:00 PM (UTC)Stadion Mašinac, Niš
Full time
What was the result of Sinđelić vs Vlasina?
Sinđelić won 2-1 on October 26, 2019.
What is the recent form of both teams?
Over their last 10 matches in all competitions, Sinđelić have 7 wins, 1 draw and 2 defeats; Vlasina have 6, 3 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 20, 2019 | Temnic 1924(away) | 2-0 | Srpska Liga - East |
| Oct 12, 2019 | Timočanin(home) | 1-0 | Srpska Liga - East |
| Oct 5, 2019 | Moravac Mrštane(away) | 3-1 | Srpska Liga - East |
| Sep 28, 2019 | Trstenik PPT(away) | 6-1 | Srpska Liga - East |
| Sep 21, 2019 | Rembas(home) | 3-1 | Srpska Liga - East |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 20, 2019 | Trstenik PPT(home) | 4-2 | Srpska Liga - East |
| Oct 13, 2019 | Rembas(away) | 1-1 | Srpska Liga - East |
| Oct 6, 2019 | Budućnost Popovac(home) | 0-0 | Srpska Liga - East |
| Sep 28, 2019 | Dubočica(away) | 2-1 | Srpska Liga - East |
| Sep 22, 2019 | Jagodina(home) | 1-2 | Srpska Liga - East |
How many goals should we expect?
Sinđelić score 1.8 and concede 0.8 goals per match over their last 10; Vlasina score 2.0 and concede 1.0.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Sinđelić | 1.8 | 0.8 | 5 | 4/10 | 4/10 |
| Vlasina | 2.0 | 1.0 | 3 | 7/10 | 7/10 |
Over the last 10 matches in all competitions.
Where do both teams sit in the table?
Sinđelić sit 7th in Srpska Liga - East (44 points from 29 matches) and Vlasina sit 10th (40 points from 29 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 7 | Sinđelić | 29 | 12 | 8 | 9 | 62 | 36 | 44 |
| 10 | Vlasina | 29 | 11 | 7 | 11 | 62 | 48 | 40 |
A question about Sinđelić vs Vlasina?
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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