KicktippAi experiment analysis

match-predictions/bundesliga-2025-26/schadensfresse/community-to-date/through-md29/community-to-date-md29

Participant names are anonymized except E.Honda and kicktipp.ai.

Task: community-to-date Primary metric: total_kicktipp_points Runs: 5 Pairings: 258

Summary

Datasetmatch-predictions/bundesliga-2025-26/schadensfresse/community-to-date/through-md29/community-to-date-md29
Task typecommunity-to-date
Primary metrictotal_kicktipp_points
Alpha0.0500

Community standings

Rank Participant Kicktipp Points p-value vs baseline
1E.Honda371
2kicktipp.ai358
3Jordan Blake350
4Kai Morgan271
5Logan Pierce0

Multi-run comparison

Friedman p-value 0.0000
E.Hondakicktipp.ai13.00000.55101.0000no35/194/29
E.HondaJordan Blake21.00000.41031.0000no46/175/37
E.HondaKai Morgan100.00000.00010.0008yes70/159/29
E.HondaLogan Pierce371.00000.00000.0000yes136/122/0
kicktipp.aiJordan Blake8.00000.72811.0000no44/171/43
kicktipp.aiKai Morgan87.00000.00110.0055yes66/155/37
kicktipp.aiLogan Pierce358.00000.00000.0000yes133/125/0
Jordan BlakeKai Morgan79.00000.00180.0072yes64/160/34
Jordan BlakeLogan Pierce350.00000.00000.0000yes134/124/0
Kai MorganLogan Pierce271.00000.00000.0000yes104/154/0

Per-item win/tie/loss counts compare paired Kicktipp points for the listed run ordering on each prepared dataset item.