Germany
Where each Bundesligateam is most likely to finish, from 1,000 Monte Carlo simulations of every remaining fixture. Each team's per-match scoring rate to date drives the Poisson model that samples goals for every unplayed match; the table aggregates position frequencies and average final points across all simulations.
Read the methodology in our model transparency page. For top-scorer race projections see Bundesliga top scorer probabilities.
| # | Team | xPts Avg | xPts Mod | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 |  Bayern München | 89.0 | 89 | 100.0 | |||||||||
| 2 |  Borussia Dortmund | 73.0 | 73 | 100.0 | |||||||||
| 3 |  RB Leipzig | 65.0 | 65 | 100.0 | |||||||||
| 4 |  VfB Stuttgart | 62.0 | 62 | 100.0 | |||||||||
| 5 |  1899 Hoffenheim | 61.0 | 61 | 100.0 | |||||||||
| 6 |  Bayer Leverkusen | 59.0 | 59 | 100.0 | |||||||||
| 7 |  SC Freiburg | 47.0 | 47 | 100.0 | |||||||||
| 8 |  Eintracht Frankfurt | 44.0 | 44 | 100.0 | |||||||||
| 9 |  FC Augsburg | 43.0 | 43 | 100.0 | |||||||||
| 10 |  FSV Mainz 05 | 40.0 | 40 | 100.0 | |||||||||
| 11 |  Union Berlin | 39.0 | 39 | ||||||||||
| 12 |  Borussia Mönchengladbach | 38.0 | 38 | ||||||||||
| 13 |  Hamburger SV | 38.0 | 38 | ||||||||||
| 14 |  1. FC Köln | 32.0 | 32 | ||||||||||
| 15 |  Werder Bremen | 32.0 | 32 | ||||||||||
| 16 |  VfL Wolfsburg | 29.0 | 29 | ||||||||||
| 17 |  1. FC Heidenheim | 26.0 | 26 | ||||||||||
| 18 |  FC St. Pauli | 26.0 | 26 |
