Vlasina vs Trstenik PPT: result 4-2 and analysis
Srpska Liga - EastEast - 10Kick-off on October 20, 2019 at 01:00 PM (UTC)Stadion Rosulja, Vlasotince
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What was the result of Vlasina vs Trstenik PPT?
Vlasina won 4-2 on October 20, 2019.
What is the recent form of both teams?
Over their last 9 matches in all competitions, Vlasina have 5 wins, 3 draws and 1 defeats; Trstenik PPT have 1, 1 and 7.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| 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 |
| Sep 14, 2019 | Toplicanin Prokuplje(away) | 2-2 | Srpska Liga - East |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 12, 2019 | Temnic 1924(home) | 5-1 | Srpska Liga - East |
| Oct 6, 2019 | Timočanin(away) | 1-1 | Srpska Liga - East |
| Sep 28, 2019 | Sinđelić(home) | 1-6 | Srpska Liga - East |
| Sep 21, 2019 | Moravac Mrštane(away) | 1-2 | Srpska Liga - East |
| Sep 15, 2019 | Rembas(away) | 0-3 | Srpska Liga - East |
How many goals should we expect?
Vlasina score 1.8 and concede 0.9 goals per match over their last 9; Trstenik PPT score 0.9 and concede 2.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Vlasina | 1.8 | 0.9 | 3 | 6/9 | 6/9 |
| Trstenik PPT | 0.9 | 2.6 | 0 | 4/9 | 6/9 |
Over the last 9 matches in all competitions.
Where do both teams sit in the table?
Vlasina sit 10th in Srpska Liga - East (40 points from 29 matches) and Trstenik PPT sit 12th (37 points from 29 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 10 | Vlasina | 29 | 11 | 7 | 11 | 62 | 48 | 40 |
| 12 | Trstenik PPT | 29 | 10 | 7 | 12 | 31 | 40 | 37 |
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