Mladost Lucani vs Radnik Surdulica: result 2-0 and analysis
Super LigaRegular Season - 8Kick-off on September 10, 2016 at 05:00 PM (UTC)Mladost Stadium Lučani, Lučani
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What was the result of Mladost Lucani vs Radnik Surdulica?
Mladost Lucani won 2-0 on September 10, 2016.
Goalscorers
- 17′M. BojovićMladost Lucani (pen.)
- 53′E. OditaMladost Lucani
What is the recent form of both teams?
Over their last 7 matches in all competitions, Mladost Lucani have 3 wins, 0 draws and 4 defeats; Radnik Surdulica have 1, 3 and 3.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 27, 2016 | Radnicki NIS(away) | 0-2 | Super Liga |
| Aug 20, 2016 | FK Vozdovac(home) | 0-1 | Super Liga |
| Aug 14, 2016 | Napredak(home) | 1-0 | Super Liga |
| Aug 10, 2016 | Metalac GM(away) | 0-2 | Super Liga |
| Aug 6, 2016 | FK Crvena Zvezda(home) | 2-4 | Super Liga |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Aug 26, 2016 | Metalac GM(home) | 0-1 | Super Liga |
| Aug 21, 2016 | FK Crvena Zvezda(away) | 0-5 | Super Liga |
| Aug 14, 2016 | Borac Cacak(home) | 1-1 | Super Liga |
| Aug 10, 2016 | RAD(away) | 0-1 | Super Liga |
| Aug 6, 2016 | FK Spartak Zdrepceva KRV(home) | 2-1 | Super Liga |
How many goals should we expect?
Mladost Lucani score 0.9 and concede 1.4 goals per match over their last 7; Radnik Surdulica score 0.7 and concede 1.6.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Mladost Lucani | 0.9 | 1.4 | 2 | 2/7 | 2/7 |
| Radnik Surdulica | 0.7 | 1.6 | 1 | 3/7 | 3/7 |
Over the last 7 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 Radnik Surdulica sit 7th (8 points from 5 matches).
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 4 | Mladost Lucani | 6 | 2 | 4 | 0 | 7 | 4 | 10 |
| 7 | Radnik Surdulica | 5 | 2 | 2 | 1 | 5 | 4 | 8 |
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