Mladost Lucani vs Vojvodina: result 2-0 and analysis
Super LigaRegular Season - 12Kick-off on October 16, 2016 at 03:00 PM (UTC)Mladost Stadium Lučani, Lučani
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What was the result of Mladost Lucani vs Vojvodina?
Mladost Lucani won 2-0 on October 16, 2016.
Goalscorers
- 5′R. ProtićMladost Lucani
- 65′S. JovanovićMladost Lucani
What is the recent form of both teams?
Over their last 11 matches in all competitions, Mladost Lucani have 6 wins, 0 draws and 5 defeats; Vojvodina have 9, 4 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 2, 2016 | FK Partizan(away) | 1-3 | Super Liga |
| Sep 25, 2016 | Backa(home) | 1-0 | Super Liga |
| Sep 17, 2016 | Novi Pazar(away) | 2-1 | Super Liga |
| Sep 10, 2016 | Radnik Surdulica(home) | 2-0 | Super Liga |
| Aug 27, 2016 | Radnicki NIS(away) | 0-2 | Super Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 2, 2016 | Metalac GM(home) | 1-0 | Super Liga |
| Sep 25, 2016 | FK Crvena Zvezda(away) | 1-4 | Super Liga |
| Sep 18, 2016 | Borac Cacak(home) | 2-1 | Super Liga |
| Sep 14, 2016 | Novi Pazar(away) | 2-1 | Super Liga |
| Sep 9, 2016 | RAD(away) | 0-0 | Super Liga |
How many goals should we expect?
Mladost Lucani score 1.1 and concede 1.3 goals per match over their last 11; Vojvodina score 1.7 and concede 0.8.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mladost Lucani | 1.1 | 1.3 | 4 | 4/11 | 4/11 |
| Vojvodina | 1.7 | 0.8 | 8 | 6/15 | 8/15 |
Over the last 11 matches in all competitions.
Where do both teams sit in the table?
Mladost Lucani sit 4th in Super Liga (10 points from 6 matches) and Vojvodina sit 2nd (12 points from 6 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Vojvodina | 6 | 4 | 0 | 2 | 10 | 6 | 12 |
| 4 | Mladost Lucani | 6 | 2 | 4 | 0 | 7 | 4 | 10 |
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