CUE Research · Study 3
The World’s Highest-Paid Athletes
Every athlete on Forbes’ highest-paid list from 2016 to 2025, by head count and by the money they earned.
The question: Do the best-paid athletes share birthdays, numbers or signs, and does the money cluster anywhere?
What stands out
No clear differences. Across every group of 50 or more and every measure, the numbers are within what chance produces.
Worth watching, not enough to claim
- Life Path
Football: Life Path 8 appears 20 times against about 10.4 expected (1.92×).
- Day energy
Everyone 2016–2025: 4 day energy appears only 8 times against about 21.5 expected.
Everyone 2016–2025: every birth quarter is within normal variation of random birthdays from the same years.
Context What explains it
Two views answer different questions. Counting people asks whether a birthday is unusually common. The money view asks where the earnings sit, and can be dominated by a few very highly paid athletes.
Birth-month effects are well documented in youth sport, where teams are grouped by age. They are weaker at the very top of individual sports and in leagues that recruit globally, so this list is a mix.
Source The data
- Forbes World’s Highest-Paid Athletes, 2016–2025. Retrieved 2026-09-27. View source
- Every athlete named on the list in any year from 2016 to 2025, counted once, with earnings summed across the years they appeared.
- Verification: 253 of 287 included. A Forbes birth date (rounded to the nearest day: Forbes stores some a few hours off) is accepted only when Forbes gives the same date every year and Wikidata records it at day precision for the matched person. Matching: English label search, restricted to humans with a sport or a sports team.
- Expected values: every day of the years each group was born in, weighted by how many people were born in each year, run through CUE’s engine. Weighting matters for Chinese signs and Life Paths, which depend on the year.
- A difference is called clear only in groups of 50 or more and at least three standard errors from expected. Because each study tests about a hundred values, a clear difference needs 3.5 standard errors; 2.5 to 3.5 is only “worth watching”.
Reproduce it: the raw data snapshots and build scripts are in CUE’s code repository (scripts/data and scripts/build-*-study.mts).
Further reading
- Forbes, The World’s Highest-Paid Athletes, 2016–2025
- Cobley, Baker, Wattie & McKenna, “Annual age-grouping and athlete development: a meta-analytical review of relative age effects in sport”, Sports Medicine 39 (2009)