Updated Wednesday Nov. 9
2022 Composite Bundesliga Rankings
Calculated by aggregating computer generated power rankings from around the web and determining each team’s average ranking.
| TEAM | AVERAGE RANKINGAVG |
1-WEEK MOVE |
PROJECTED POINTS |
WIN LEAGUE |
|
|---|---|---|---|---|---|
| 1 |
Bayern MunichBMU31 pts
|
1.00 | - | 78.5 | 89% |
| 2 |
RB LeipzigRBL25 pts
|
2.00 | - | 61.0 | 4% |
| 3 |
DortmundBVB25 pts
|
3.67 | - | 60.0 | 3% |
| 4 |
EintrachtFRA26 pts
|
4.00 | ↑ 1 | 58.0 | 1% |
| 5 |
SC FreiburgFRE27 pts
|
4.67 | ↓ 1 | 57.5 | 1% |
| 6 |
LeverkusenLEV15 pts
|
6.67 | ↑ 1 | 44.5 | <1% |
| 7 |
Union BerlinFCUB27 pts
|
7.00 | ↓ 1 | 55.5 | <1% |
| 8 |
WolfsburgWLF20 pts
|
7.33 | ↑ 1 | 48.0 | <1% |
| 9 |
HoffenheimHOF18 pts
|
9.67 | ↓ 1 | 44.0 | <1% |
| 10 |
MainzMNZ18 pts
|
10.33 | - | 43.5 | <1% |
| 11 |
GladbachMGB19 pts
|
11.00 | - | 45.0 | <1% |
| 12 |
VfB StuttgartSTU14 pts
|
12.33 | - | 36.5 | <1% |
| 13 |
1. FC KölnCOL17 pts
|
12.67 | - | 41.0 | <1% |
| 14 |
Werder BremenBRE21 pts
|
12.67 | - | 44.0 | <1% |
| 15 |
FC AugsburgAUG15 pts
|
15.33 | - | 35.5 | <1% |
| 16 |
Hertha BSCHER11 pts
|
16.33 | - | 32.0 | <1% |
| 17 |
VfL BochumBOC10 pts
|
16.67 | - | 30.0 | <1% |
| 18 |
Schalke 04SCH9 pts
|
17.67 | - | 26.0 | <1% |
How We Calculate: Our Bundesliga Composite Power Rankings are calculated by aggregating computer rankings from around the web and determining each team’s average ranking. Up or down movement within our rankings versus the previous week is provided for each team. Some of these sites also project teams’ future success. We collect this info and calculate each team’s average total points projection and Bundesliga title odds.
Our heat chart below shows how each of the three sites we pull from ranks all 18 teams. We pull from FiveThirtyEight (538), Massey Ratings (MY) and Euro Club Index (ECI).
| SITES PULLED FROM | ||||
|---|---|---|---|---|
| TEAM | 538 | MY | ECI | AVERAGEAVG |
| Bayern MunichBMU | 1 | 1 | 1 | 1.00 |
| RB LeipzigRBL | 2 | 2 | 2 | 2.00 |
| DortmundBVB | 3 | 5 | 3 | 3.67 |
| EintrachtFRA | 4 | 4 | 4 | 4.00 |
| SC FreiburgFRE | 6 | 3 | 5 | 4.67 |
| LeverkusenLEV | 5 | 8 | 7 | 6.67 |
| Union BerlinFCUB | 9 | 6 | 6 | 7.00 |
| WolfsburgWLF | 7 | 7 | 8 | 7.33 |
| HoffenheimHOF | 10 | 9 | 10 | 9.67 |
| MainzMNZ | 8 | 12 | 11 | 10.33 |
| GladbachMGB | 11 | 13 | 9 | 11.00 |
| VfB StuttgartSTU | 13 | 10 | 14 | 12.33 |
| 1. FC KölnCOL | 12 | 14 | 12 | 12.67 |
| Werder BremenBRE | 14 | 11 | 13 | 12.67 |
| FC AugsburgAUG | 16 | 15 | 15 | 15.33 |
| Hertha BSCHER | 15 | 17 | 17 | 16.33 |
| VfL BochumBOC | 18 | 16 | 16 | 16.67 |
| Schalke 04SCH | 17 | 18 | 18 | 17.67 |
Standard deviation is a statistical tool used to measure the variance within a set of numbers. In the table below, we use standard deviation to determine which teams are ranked the most and least consistently. A low number indicates that a team is ranked consistently across the five sites we pull from. A high number indicates an inconsistently ranked team.
| SITES PULLED FROM | ||||
|---|---|---|---|---|
| TEAM | 538 | MY | ECI | STAN DEVSTDEV |
| Bayern MunichBMU | 1 | 1 | 1 | 0.000 |
| RB LeipzigRBL | 2 | 2 | 2 | 0.000 |
| EintrachtFRA | 4 | 4 | 4 | 0.000 |
| FC AugsburgAUG | 16 | 15 | 15 | 0.577 |
| Schalke 04SCH | 17 | 18 | 18 | 0.577 |
| HoffenheimHOF | 10 | 9 | 10 | 0.577 |
| WolfsburgWLF | 7 | 7 | 8 | 0.577 |
| 1. FC KölnCOL | 12 | 14 | 12 | 1.155 |
| VfL BochumBOC | 18 | 16 | 16 | 1.155 |
| Hertha BSCHER | 15 | 17 | 17 | 1.155 |
| DortmundBVB | 3 | 5 | 3 | 1.155 |
| LeverkusenLEV | 5 | 8 | 7 | 1.528 |
| SC FreiburgFRE | 6 | 3 | 5 | 1.528 |
| Werder BremenBRE | 14 | 11 | 13 | 1.528 |
| Union BerlinFCUB | 9 | 6 | 6 | 1.732 |
| GladbachMGB | 11 | 13 | 9 | 2.000 |
| VfB StuttgartSTU | 13 | 10 | 14 | 2.082 |
| MainzMNZ | 8 | 12 | 11 | 2.082 |
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