01 The birthday¶
Birthdays are arbitrary. I stopped liking every “Happy Birthday!” comment on my Facebook wall somewhere around 2012. We all hear that the last meaningful birthday is 25 because you can rent a car without paying extra for it. That was a decade ago for me. Shit.
As discovered a few decades back though, birthdays can matter…quite a bit. In 1985 Paula Barnsley noticed something strange at a junior hockey game while reading the program. Nearly every player was born in January, February and March.
Forty years later and things haven’t changed much. As pointed out by Gladwell in his book Outliers, this was due to a “relative age effect”. Canada has a strict January 1st cutoff for its youth hockey league, meaning a child born on December 31st is almost a year younger than a child born January 1st. That slight edge means a January baby has an advantage growing up (taller, bigger, faster) and is likely afforded more opportunities along the way.
What hasn’t fully been examined, however, is whether this relative age effect exists in other American sports.
- NFL
- MLB
- NBA
- NHL
We looked into this (see data above) and found that of the four biggest American sports, the relative age effect only existed in hockey. Football, basketball, and baseball were all flat. Soccer is a little different.
Before 2016, USA Soccer grouped kids by school year with an August 1st cutoff. If we look at the birth months of pro American soccer players from that era, they are flat, that is, there is no relative age effect. Then in 2016 US Soccer moved to a January 1st birth-year cutoff to line up with FIFA. Take a look at the results…
Within a decade Team USA Soccer became disproportionately populated with players born earlier in the year. This gives rise to the belief that small (seemingly insignificant) advantages can compound, the Matthew Effect as it’s often referred to. Where else might these edges exist?
02 Where you’re born¶
Growing up in rural Pennsylvania, I was a wrestler. If you’re familiar with the movie “Foxcatcher”, it gives you an idea of the Pennsylvanian wrestling culture. The movie follows John du Pont, a wealthy wrestling-obsessed man who built a massive 14,000 sq. ft. training center on his property for elite wrestlers. More kids wrestle in Ohio and Pennsylvania than any other part of the country.
The same idea exists on a much grander scale in the South, except what “just means more” is football.
Check out where pro athletes come from below:
Hometowns of NFL players with a first pro season of 1990 or later, matched to their home county.
Per capita, the South produces almost double the NFL players of any other region. Louisiana alone produces three times the national rate of NFL players. The Northeast, for its part, is not big on contact (not a lot of heat in the map above, as you’ll see).
Clearly, this is cultural. Professional athletes follow suit. If we look at who produces the most baseball players, it’s Little League’s birthplace, Pennsylvania. Meanwhile, NHL players tend to come from where the lakes freeze over. Despite having 10,000+ lakes, there is nothing in the water that leads to Minnesota having twelve times the national rate of NHL players. Instead, it has a lot more to do with the fact that those lakes freeze over.
The best athletes pursue whatever sport their place cares about most.
But there is a new relative effect…one far more significant.
03 Income¶
Michael and I were discussing the relative age effect and he brought up a question: are pro athletes coming from wealthier areas now?
If you go back to the 1990s, about 43% of NFL players came from the poorest quarter of American towns. That share has fallen every decade since. It’s now down to 33% in the 2020s. Over the same stretch, the share coming from the richest quarter more than doubled, going from 10% to 25%.
Traditionally, the NFL has been one of the harder sports to price athletes out of. While the equipment is expensive, Pop Warner is often free to those who can’t afford it. It’s also incredibly well organized at the community level. Despite that, we are seeing a pretty big shift: over the past few decades, more and more NFL players are coming from wealthy hometowns. One interesting pattern is that positions differ significantly.
If we look at the wealthiest quartile over the last three decades, 43% of kickers and punters now come from the richest quarter of American hometowns. Quarterbacks have also skyrocketed to 38%. These are “high skill” positions that can be somewhat molded with money, at least more so than other football positions. A four-day session at the Mannings’ passing academy already ran $575 with room and board over a decade ago. A week at IMG Academy’s football camp starts at around $2,400 today. Camps like these buy elite coaching and development, of course, skills trainers are likely where the biggest strides are made (both in terms of cost, and development).
The shift is far more dramatic in the heavy-skill sports. In baseball, the share of MLB players coming from the richest American hometowns has climbed to roughly 30%, more than double where it sat in the 1990s.
Baseball is unlike football in that it is heavily skill dependent. There are only so many 6’5” guys running 4.5 sec 40s, however, we can all throw. Facilities like Driveline Baseball will engineer an arm for you (check out Michael’s video on the evolution of throwing if you haven’t) and travel teams will let you play year round. For a cost. Michael shared with me that his neighbor has traveled to five states this year for baseball. He’s in 6th grade.
We also looked at differences between hitting and pitching, and one might guess that pitching, the most engineerable role, skews the richest. It does not: pitchers and hitters come from almost exactly the same income mix.
How about the sport on skates? In the 1990s hockey was close to even, with more than 30% of US-born NHL players coming from the poorest hometowns. That number has plummeted, today, about 10% of the NHL is comprised of athletes coming from the poorest hometowns.
Meanwhile, nearly half (!) of the NHL is coming from the richest hometowns. Hockey lives at the extremes. It is played at the most extreme temperature, it has the most significant Relative Age Effect, and it is the most expensive sport to play. Junior hockey regularly costs north of $20,000 per child, unless you live in Minnesota, where many municipal hockey rinks still stand. Unsurprisingly, Minnesota produces by far the most hockey players.
Basketball is an interesting one. You have to be tall, and tall can come from anywhere, but increasingly it comes from wealthier areas: over 44% of NBA players came from the poorest hometowns in the 1990s. That’s down about a third today, meanwhile the richest quartile has more than doubled over the last thirty years.
04 Steph, Bronny, and what money shouldn’t buy¶
Fundamentally, we should want this. The Matthew Effect promises a nonlinear payoff: a little bit of early investment can compound into much larger returns. As we have progressed as a society, we have learned how to invest and train our youth in ways that are building better athletes than ever before. In that sense, nurture is fighting back against nature. Unfortunately, there are some complications to this…
Daniel Markovits, author of The Meritocracy Trap, frames accomplishment as the product of three inputs: effort, talent, and training. That last element, training, is so unequal today that “equal opportunity” is becoming unfairly nuanced, even in the ultimate meritocratic playground that is sports. The kids who have parents with enough time and/or money are getting significantly better training and development, leading to a new age of professional athletes.10
Maybe you don’t think this is really a problem, and to be fair, there are a lot more important things in life than worrying about professional athletes. Sadly, as we’ll explore in the next article, new data is showing that this is happening in far more arenas than just sports…
Nick and Michael
Sources¶
- Barnsley, R. H., Thompson, A. H., & Barnsley, P. E. (1985). Hockey success and birthdate: The relative age effect. CAHPER Journal, 51, 23–28. ↩
- Modern NHL birth dates: author’s compilation from the NHL’s public player API, n = 6,106 players active since the 1989–90 season with a recorded birth date, 2026. Birth quarters cut on the January 1 minor-hockey age cutoff run 32, 28, 22, 19% from Q1 to Q4; the “deficit” is the count of late-born players below an even 25%-per-quarter line (about 595 across the sample, roughly 1 in 10), scaled to a ˜700-player active league. ↩
- Musch, J., & Grondin, S. (2001). Unequal competition as an impediment to personal development: A review of the relative age effect in sport. Developmental Review, 21(2), 147–167. On the “Matthew effect” framing, see also Merton, R. K. (1968), Science, 159, 56–63. ↩
- US soccer player birth months compiled from Wikidata: cohorts born 1985–1999 (August 1 school-year cutoff era, n = 4,114) and 2003–2009 (January 1 cutoff, n = 721); cutoff change per US Soccer Federation birth-year registration, effective 2016. The new-cutoff cohort is small and recent, so read the direction, not the decimals. Author’s calculation. ↩
- Bedard, K., & Dhuey, E. (2006). The persistence of early childhood maturity: International evidence of long-run age effects. Quarterly Journal of Economics, 121(4), 1437–1472; Figlio, D., Karbownik, K., & Roth, J. (2017), NBER Working Paper 23660 (Florida school records).
- Black, S. E., Devereux, P. J., & Salvanes, K. G. (2008). Too young to leave the nest? The effects of school starting age. NBER Working Paper 13969 (Norway). Consistent with several US and European studies.
- Player production by region, state and county: author’s calculation, 2026. NFL from nflverse rosters, ESPN birthplaces and Sleeper high-school records (hometown = high-school county where known, otherwise birth county); MLB from the Lahman database; NHL from the NHL’s public player API; NBA from Basketball-Reference; matched to US Census Bureau county and state population estimates (vintage 2024). First pro seasons 1990–2025; per-capita charts are US-born players; 96–98% of players match a Census place in every era (NHL 87–92%). ↩
- Players by hometown median-household-income quartile: author’s calculation, 2026. Hometowns are Census places (for the NFL, the high-school town where known, otherwise birthplace); quartiles are population-weighted within era-matched income vintages (2000 Census income for 1990s–2000s cohorts, ACS 2023 for later), so the richest quarter always holds the places where the richest quarter of Americans live. US-born players, first pro seasons 1990–2025: n ≈ 13,400 NFL, 5,600 MLB, 2,300 NBA, 980 NHL. Position splits: 2020s quarterbacks n = 117 (38%), kickers and punters n = 76 (43%). Income is the hometown’s median, not the player’s family income; NHL cells are small (as few as 20 players), so read exact shares loosely. ↩
- Pew Research Center (2023). Americans’ views on considering race and ethnicity in college admissions.
- Markovits, D. (2019). The Meritocracy Trap. Penguin Press. ↩
- On Oxford’s socioeconomic intake, see the University of Oxford Undergraduate Admissions Statistical Report. Oxford does not publish an average family income; the “twice the UK average” figure is not from Oxford’s own data, which tracks school type, free-school-meal eligibility and area deprivation.
- College Board (2013), SAT scores by family income band, College-Bound Seniors Total Group Profile Report; author’s chart.
- Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor. In Whither Opportunity? (Duncan & Murnane, eds.).
- Chetty, R., Grusky, D., Hell, M., Hendren, N., Manduca, R., & Narang, J. (2017). The fading American dream: Trends in absolute income mobility since 1940. Science, 356(6336), 398–406.
- Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the land of opportunity? Quarterly Journal of Economics, 129(4); relative-mobility framing per Scott Winship. Transition figures are the author’s calculation from the released copula.
- Dale, S. B., & Krueger, A. B. (2002), Quarterly Journal of Economics, 117(4); and (2014), Journal of Human Resources, 49(2).
- Per-pupil spending: US Census Bureau, Annual Survey of School System Finances, FY2024, and NCES.
- Reading and math rankings (demographically adjusted): NAEP 2024, via the Urban Institute’s adjustment and reporting by Nicholas Kristof, The New York Times. Spending-vs-outcome scatter: author’s calculation.
- Kristof, N., The New York Times, on Mississippi’s literacy reforms; Mississippi Department of Education.
- Youth age-determination dates: Little League Baseball (August 31) and Pop Warner Football (July 31), per each organisation’s published age-determination rules. Basketball is generally grouped by school grade, which varies by district. ↩
- Elite position-camp pricing: Manning Passing Academy tuition $420 (day) / $575 (overnight) for the four-day 2013 session, per WWNO public radio’s reporting; IMG Academy football camps from $2,399 per week, 2026 season pricing per IMG Academy. ↩
- Lindbergh, B., & Sawchik, T. (2019). The MVP Machine: How Baseball’s New Nonconformists Are Using Data to Build Better Players. Basic Books; on Driveline Baseball and the paid player-development industry. ↩
- Gladwell, M. (2008). Outliers: The Story of Success. Little, Brown and Company; the book that made the relative age effect famous. ↩
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