FK Crvena Zvezda vs TSC Backa Topola: result 3-1 and analysis
Super LigaRegular Season - 14Kick-off on October 30, 2019 at 05:00 PM (UTC)Stadion Rajko Mitić, Beograd
Full time
What was the result of FK Crvena Zvezda vs TSC Backa Topola?
FK Crvena Zvezda won 3-1 on October 30, 2019.
Goalscorers
- 12′TómanéFK Crvena Zvezda
- 44′S. GrabežFK Crvena Zvezda (o.g.)
- 63′JanderTSC Backa Topola (o.g.)
- 78′V. SimićFK Crvena Zvezda
What is the recent form of both teams?
Over their last 15 matches in all competitions, FK Crvena Zvezda have 9 wins, 3 draws and 3 defeats; TSC Backa Topola have 8, 5 and 2.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 26, 2019 | Radnik Surdulica(away) | 5-0 | Super Liga |
| Oct 22, 2019 | Tottenham(away) | 0-5 | UEFA Champions League |
| Oct 18, 2019 | RAD(home) | 3-1 | Super Liga |
| Oct 6, 2019 | Napredak(away) | 1-0 | Super Liga |
| Oct 1, 2019 | Olympiakos Piraeus(home) | 3-1 | UEFA Champions League |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 27, 2019 | Proleter Novi SAD(home) | 1-1 | Super Liga |
| Oct 19, 2019 | Javor(away) | 2-3 | Super Liga |
| Oct 5, 2019 | Radnik Surdulica(away) | 0-1 | Super Liga |
| Sep 29, 2019 | RAD(home) | 2-0 | Super Liga |
| Sep 21, 2019 | Napredak(away) | 3-1 | Super Liga |
How many goals should we expect?
FK Crvena Zvezda score 2.0 and concede 1.5 goals per match over their last 15; TSC Backa Topola score 1.7 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| FK Crvena Zvezda | 2.0 | 1.5 | 2 | 10/15 | 12/15 |
| TSC Backa Topola | 1.7 | 0.9 | 5 | 9/15 | 7/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | FK Crvena Zvezda | 4 | 4 | 0 | 0 | 14 | 1 | 12 |
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