Bayern München vs FK Crvena Zvezda: result 3-0 and analysis
UEFA Champions LeagueGroup Stage - 1Kick-off on September 18, 2019 at 07:00 PM (UTC)Allianz Arena, München
Full time
What was the result of Bayern München vs FK Crvena Zvezda?
Bayern München won 3-0 on September 18, 2019.
Goalscorers
- 34′K. ComanBayern München
- 80′R. LewandowskiBayern München
- 90′T. MüllerBayern München
What is the recent form of both teams?
Over their last 15 matches in all competitions, Bayern München have 9 wins, 4 draws and 2 defeats; FK Crvena Zvezda have 9, 5 and 1.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 14, 2019 | RB Leipzig(away) | 1-1 | Bundesliga |
| Aug 31, 2019 | FSV Mainz 05(home) | 6-1 | Bundesliga |
| Aug 24, 2019 | FC Schalke 04(away) | 3-0 | Bundesliga |
| Aug 16, 2019 | Hertha BSC(home) | 2-2 | Bundesliga |
| Aug 12, 2019 | Energie Cottbus(away) | 3-1 | DFB Pokal |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Sep 14, 2019 | Indjija(home) | 2-1 | Super Liga |
| Aug 31, 2019 | Vojvodina(away) | 2-1 | Super Liga |
| Aug 27, 2019 | BSC Young Boys(home) | 1-1 | UEFA Champions League |
| Aug 21, 2019 | BSC Young Boys(away) | 2-2 | UEFA Champions League |
| Aug 17, 2019 | FK Spartak Zdrepceva KRV(away) | 3-2 | Super Liga |
How many goals should we expect?
Bayern München score 2.3 and concede 1.0 goals per match over their last 15; FK Crvena Zvezda score 1.8 and concede 0.9.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Bayern München | 2.3 | 1.0 | 4 | 10/15 | 10/15 |
| FK Crvena Zvezda | 1.8 | 0.9 | 6 | 9/15 | 8/15 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 2 | Bayern München | 8 | 7 | 0 | 1 | 22 | 8 | 21 |
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