Leagues

League · Germany

2. Bundesliga 2023-24 statistics

2023-24 season

Matches played
306
Goals per match
3.09
Home win
46%
Draw
23%
Away win
31%
3+ goals
61%
Both teams scored
59%

Table

#TeamPWDLGFGAGDPts
1FC St. Pauli3420956236+2669
2Holstein Kiel3421586539+2668
3Fortuna Düsseldorf3418977240+3263
4Hamburger SV34177106444+2058
5Karlsruher SC34151096848+2055
6Hannover 9634131385944+1552
7SC Paderborn 0734157125454052
8SpVgg Greuther Fürth34148125049+150
9Hertha BSC34139126959+1048
10FC Schalke 0434127155360-743
11SV Elversberg34127154963-1443
121. FC Nürnberg34117164364-2140
131. FC Kaiserslautern34116175964-539
141. FC Magdeburg34911144654-838
15Eintracht Braunschweig34115183753-1638
16SV Wehen3488183650-1432
17Hansa Rostock3494213057-2731
18VfL Osnabrück34610183169-3828

The table is computed from match results; matches decided by forfeit count with the score declared by the federation. Points deducted or awarded separately are not reflected. Only regular-season matches count — play-offs and relegation matches are excluded.

Teams in this league

Every team in this season's fixture list. Unlike the standings table, teams that have not played yet also appear here.

Season simulation

The remaining fixtures were played out 10,000 times using the model's current probabilities. Percentages below are how often each team finished in that position.

TeamTitleTop 4Bottom 3Pts (avg)
1. FC Nürnberg33.3%70.4%0.2%59.5
Hertha BSC10.2%39.1%1.2%53.9
VfL Wolfsburg9.6%38.3%1.3%53.8
Arminia Bielefeld8.1%35.9%1.6%53.0
Dynamo Dresden5.6%29.1%2.8%51.8
Hannover 965.9%29.3%2.4%51.8
VfL Bochum4.9%26.2%2.7%51.3
FC St. Pauli4.2%21.7%3.8%50.2
SV Darmstadt 984.3%22.2%3.8%50.1
1. FC Kaiserslautern3.3%18.8%4.8%49.4
Karlsruher SC3.3%18.4%5.4%49.3
Holstein Kiel2.9%16.7%5.8%48.8
Energie Cottbus2.5%15.3%6.1%48.6
1. FC Magdeburg1.3%10.4%10.4%46.7
Eintracht Braunschweig0.6%6.2%15.3%44.4
SpVgg Greuther Fürth0.1%2.1%34.1%40.7
1. FC Heidenheim0.0%0.0%98.2%24.3
VfL Osnabrück0.0%0.0%99.9%17.9

Method: ratings are frozen as of the run date; ties break by points-GD-goals, country-specific rules not applied. Pairings below the publishing threshold use the model's prior rating. The table refreshes whenever the script is re-run.

Generated: 2026-08-23 · 3 · 10,000

The model's record in this league

The model's claim is not “I know every match” — it is “I know where I'm confident”. Measured in this league:

Match result
Model at leastPredictionsRealised
50%37457%
60%10768%
70%2273%
Double chance
Model at leastPredictionsRealised
75%81879%
80%21486%
85%6088%
Goals markets
Model at leastPredictionsRealised
50%219960%
55%192061%
60%125463%

And if it had to answer every match?

Model
49%
Always pick home
44%
Picking at random
33%
Reachable ceiling
75%

Why that ceiling is not 100%: 25% of matches in this league end in a draw, and a draw is almost never the single most likely outcome on its own. So one “accuracy” figure cannot be read on its own — it is read next to these anchors.

Matches measured: 1149. The thresholds were not cherry-picked — all of them are shown. Incorrect predictions are included and none are hidden.

Full track record

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