Updated Monday Mar. 20
2023 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 MunichBMU52 pts
|
1.00 | - | 72.5 | 73% |
| 2 |
DortmundBVB53 pts
|
2.33 | ↑ 1 | 69.5 | 13% |
| 3 |
RB LeipzigRBL45 pts
|
2.67 | ↓ 1 | 61.5 | 13% |
| 4 |
LeverkusenLEV37 pts
|
4.67 | ↑ 1 | 51.0 | <1% |
| 5 |
Union BerlinFCUB48 pts
|
6.00 | ↓ 1 | 61.5 | <1% |
| 6 |
EintrachtFRA40 pts
|
6.67 | - | 54.5 | <1% |
| 7 |
WolfsburgWLF38 pts
|
7.00 | ↑ 1 | 52.0 | <1% |
| 8 |
SC FreiburgFRE46 pts
|
7.00 | ↓ 1 | 58.5 | <1% |
| 9 |
MainzMNZ37 pts
|
8.00 | - | 48.0 | <1% |
| 10 |
GladbachMGB31 pts
|
9.67 | - | 42.5 | <1% |
| 11 |
1. FC KölnCOL27 pts
|
11.33 | - | 38.0 | <1% |
| 12 |
VfB StuttgartSTU20 pts
|
13.00 | - | 30.5 | <1% |
| 13 |
HoffenheimHOF22 pts
|
13.33 | ↑ 1 | 32.0 | <1% |
| 14 |
Werder BremenBRE31 pts
|
13.33 | ↓ 1 | 40.5 | <1% |
| 15 |
FC AugsburgAUG28 pts
|
14.67 | - | 36.5 | <1% |
| 16 |
VfL BochumBOC25 pts
|
16.33 | ↑ 1 | 34.0 | <1% |
| 17 |
Schalke 04SCH21 pts
|
17.00 | ↑ 1 | 29.5 | <1% |
| 18 |
Hertha BSCHER21 pts
|
17.00 | ↓ 2 | 29.5 | <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 |
| DortmundBVB | 3 | 2 | 2 | 2.33 |
| RB LeipzigRBL | 2 | 3 | 3 | 2.67 |
| LeverkusenLEV | 4 | 5 | 5 | 4.67 |
| Union BerlinFCUB | 10 | 4 | 4 | 6.00 |
| EintrachtFRA | 7 | 7 | 6 | 6.67 |
| WolfsburgWLF | 5 | 8 | 8 | 7.00 |
| SC FreiburgFRE | 8 | 6 | 7 | 7.00 |
| MainzMNZ | 6 | 9 | 9 | 8.00 |
| GladbachMGB | 9 | 10 | 10 | 9.67 |
| 1. FC KölnCOL | 12 | 11 | 11 | 11.33 |
| VfB StuttgartSTU | 11 | 12 | 16 | 13.00 |
| HoffenheimHOF | 13 | 15 | 12 | 13.33 |
| Werder BremenBRE | 14 | 13 | 13 | 13.33 |
| FC AugsburgAUG | 16 | 14 | 14 | 14.67 |
| VfL BochumBOC | 18 | 16 | 15 | 16.33 |
| Schalke 04SCH | 15 | 18 | 18 | 17.00 |
| Hertha BSCHER | 17 | 17 | 17 | 17.00 |
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 | 17 | 17 | 17 | 0.000 |
| RB LeipzigRBL | 2 | 3 | 3 | 0.577 |
| Werder BremenBRE | 14 | 13 | 13 | 0.577 |
| 1. FC KölnCOL | 12 | 11 | 11 | 0.577 |
| DortmundBVB | 3 | 2 | 2 | 0.577 |
| GladbachMGB | 9 | 10 | 10 | 0.577 |
| EintrachtFRA | 7 | 7 | 6 | 0.577 |
| LeverkusenLEV | 4 | 5 | 5 | 0.577 |
| SC FreiburgFRE | 8 | 6 | 7 | 1.000 |
| FC AugsburgAUG | 16 | 14 | 14 | 1.155 |
| VfL BochumBOC | 18 | 16 | 15 | 1.528 |
| HoffenheimHOF | 13 | 15 | 12 | 1.528 |
| MainzMNZ | 6 | 9 | 9 | 1.732 |
| Schalke 04SCH | 15 | 18 | 18 | 1.732 |
| WolfsburgWLF | 5 | 8 | 8 | 1.732 |
| VfB StuttgartSTU | 11 | 12 | 16 | 2.646 |
| Union BerlinFCUB | 10 | 4 | 4 | 3.464 |
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