Updated Monday Aug. 8
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 MunichBMU3 pts
|
1.00 | - | 80.0 | 70% |
| 2 |
SC FreiburgFRE3 pts
|
5.00 | ↑ 3 | 49.5 | 1% |
| 3 |
RB LeipzigRBL1 pts
|
5.33 | - | 59.5 | 8% |
| 4 |
DortmundBVB3 pts
|
6.67 | ↑ 4 | 62.5 | 9% |
| 5 |
GladbachMGB3 pts
|
7.00 | ↑ 6 | 49.5 | 2% |
| 6 |
LeverkusenLEV0 pts
|
7.33 | ↓ 4 | 54.0 | 3% |
| 7 |
WolfsburgWLF1 pts
|
7.33 | ↓ 3 | 43.5 | <1% |
| 8 |
1. FC KölnCOL3 pts
|
8.33 | ↑ 2 | 44.5 | <1% |
| 9 |
Union BerlinFCUB3 pts
|
8.33 | ↓ 2 | 49.0 | 2% |
| 10 |
EintrachtFRA0 pts
|
8.67 | ↓ 4 | 47.5 | 1% |
| 11 |
MainzMNZ3 pts
|
9.33 | ↑ 1 | 45.5 | <1% |
| 12 |
HoffenheimHOF0 pts
|
9.67 | ↓ 3 | 41.5 | <1% |
| 13 |
VfB StuttgartSTU1 pts
|
10.33 | - | 38.0 | <1% |
| 14 |
Werder BremenBRE1 pts
|
11.33 | ↑ 1 | 39.0 | <1% |
| 15 |
VfL BochumBOC0 pts
|
14.67 | ↓ 1 | 34.0 | <1% |
| 16 |
FC AugsburgAUG0 pts
|
16.33 | - | 33.5 | <1% |
| 17 |
Hertha BSCHER0 pts
|
17.00 | ↑ 1 | 33.5 | <1% |
| 18 |
Schalke 04SCH0 pts
|
17.33 | ↓ 1 | 34.5 | <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 |
| SC FreiburgFRE | 7 | 2 | 6 | 5.00 |
| RB LeipzigRBL | 2 | 11 | 3 | 5.33 |
| DortmundBVB | 3 | 15 | 2 | 6.67 |
| GladbachMGB | 5 | 8 | 8 | 7.00 |
| LeverkusenLEV | 4 | 14 | 4 | 7.33 |
| WolfsburgWLF | 10 | 3 | 9 | 7.33 |
| 1. FC KölnCOL | 9 | 4 | 12 | 8.33 |
| Union BerlinFCUB | 6 | 12 | 7 | 8.33 |
| EintrachtFRA | 11 | 10 | 5 | 8.67 |
| MainzMNZ | 8 | 9 | 11 | 9.33 |
| HoffenheimHOF | 12 | 7 | 10 | 9.67 |
| VfB StuttgartSTU | 13 | 5 | 13 | 10.33 |
| Werder BremenBRE | 14 | 6 | 14 | 11.33 |
| VfL BochumBOC | 15 | 13 | 16 | 14.67 |
| FC AugsburgAUG | 17 | 17 | 15 | 16.33 |
| Hertha BSCHER | 16 | 18 | 17 | 17.00 |
| Schalke 04SCH | 18 | 16 | 18 | 17.33 |
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 |
| Hertha BSCHER | 16 | 18 | 17 | 1.000 |
| FC AugsburgAUG | 17 | 17 | 15 | 1.155 |
| Schalke 04SCH | 18 | 16 | 18 | 1.155 |
| VfL BochumBOC | 15 | 13 | 16 | 1.528 |
| MainzMNZ | 8 | 9 | 11 | 1.528 |
| GladbachMGB | 5 | 8 | 8 | 1.732 |
| HoffenheimHOF | 12 | 7 | 10 | 2.517 |
| SC FreiburgFRE | 7 | 2 | 6 | 2.646 |
| Union BerlinFCUB | 6 | 12 | 7 | 3.215 |
| EintrachtFRA | 11 | 10 | 5 | 3.215 |
| WolfsburgWLF | 10 | 3 | 9 | 3.786 |
| 1. FC KölnCOL | 9 | 4 | 12 | 4.041 |
| VfB StuttgartSTU | 13 | 5 | 13 | 4.619 |
| Werder BremenBRE | 14 | 6 | 14 | 4.619 |
| RB LeipzigRBL | 2 | 11 | 3 | 4.933 |
| LeverkusenLEV | 4 | 14 | 4 | 5.774 |
| DortmundBVB | 3 | 15 | 2 | 7.234 |
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