Part II: The NBA/WNBA wage gap explored via economies of scale, participation gaps, and professional chess.

This is a three-part essay that uses statistics and proprietary data to explore how the NBA and WNBA’s biggest stars align, why (despite their similarities) they’re paid differently, and why their differences in style and strategy is something to celebrate. Ultimately, my hope is that readers will come away with a better understanding of the inequalities and gendered differences that underpin professional basketball.

The author is me, Josh Strupp — product designer at Taoti Creative by day, data hobbyist the rest of the time.

  • Outlier Status: A glance at superstardom.
  • Superstar Similarities: Which NBA and WNBA players are (nearly) statistically identical?
  • Systemic Biases: Economies of scale, participation gaps, and more red flags as seen through chess, the MLS, and eSports.
  • Stylistic Disparities: how the WNBA’s strategy is better for fans and a data-driven look at “hero ball.”
  • In Conclusion: Thoughts on the latest WNBA collective bargaining agreement, a plea to engage with the sport, and a Kobe quote.
  • Glossary: includes listing of all abbrevitions used for stat categories (e.g. USG%, PER, PTS, etc).
  • Spreadsheet: Includes all 30,000 player comparisons and economic data leveraged to write Part II.

Systemic Biases: Economies of scale, participation gaps, and more red flags.

In Part I, we explored NBA and WNBA outliers and how they’re alike using a stat matcher of my own design. Statistical doppelgängers were revealed, underscoring the shared dominance between players like Stephen Curry and Leilani Mitchell, or Kevin Durant and Elena Delle Donne.

In Part II, we’ll explore the nuances and reasons behind disproportional pay, despite their statistical similarities. What follows are three data-driven (but opinionated) reasons for this gap.

We’ll start by comparing the WNBA and NBA to other major sports leagues to see if payment is consistent given the size and scale of a given league. Then we’ll look at participation gaps in professional chess as an explainer for perceived differences in talent. Then we’ll pit the WNBA against a comparable organization: major league soccer. Finally, we’ll end on a note about ownership structure.

Are WNBA players paid appropriately considering the size and commercial success of the game? Can we compare them to the MLS, NHL, MLB — even a professional eSports league — to see if there is a wage gap based on gender alone? Is the size and financial prowess of a league proportional to the amount it pays its players?

To answer these questions, we can compare the WNBA with other professional sports leagues and factor in things like total revenue, aggregate players, average salary and number of teams. We can then begin to measure how fairly each league is paying their players.

You’ll notice that as a league makes more revenue (dark blue), it can pay its players more money (light blue). But it’s not linear — it’s exponential. By linear standards, if the average WNBA player makes $75,000, then the average NBA player would make somewhere around $3.4M (half of the actual average salary).

Let’s see the data as a scatter plot with a trend line.

Note: for what it’s worth, there is another major female sports league — the National Women’s Soccer League — but their maximum salary is so low ($50,000) and financial figures so inaccessible that they were omitted from this data.

Notice the R² number next to the top of the trend line. The R² coefficient is a gauge for how closely each data point fits the line. The closer it is to 1, the better the data fits. Our R² coefficient is .96, which indicates that each league is paying its players appropriately proportional to the number of players and the amount of revenue they bring in.

You’ll also notice that the WNBA is in the very bottom corner of this curve. Of the leagues we researched, only the Canadian Football League (CFL) occupies that spot on the curve.

According to this data set, WNBA players make just as much as you would expect athletes to make based on total league revenue; in essence, their wages are “fair.” Other female athletes have seen this explanation used to justify their unequal pay: when the US Women’s National Soccer Team (ranked number 1 in the world) filed a class action lawsuit against the US Soccer Federation alleging that they’re paid and supported unfairly, the federation blamed economics:

The soccer federation denied the claims in the women’s lawsuit, arguing in a May court filing that the pay differential between the men and women players is “based on differences in aggregate revenue generated by the different teams and/or any other factor other than sex” and that the two teams are “physically and functionally separate organizations.”

Yes, revenue matters. But — once again — that’s not the whole story. Economic standards are far from the only things we should be measuring.

Is it really that there’s less interest? Are male basketball players just more entertaining? Do they simply possess more talent that draws larger crowds? After all, professional female and male basketball players play the exact same game (albeit, with different approaches). So how much does gender factor into the gaps in revenue and respect?

Fans of Netflix miniseries The Queen’s Gambit might appreciate this next bit.

In the world of professional chess, there exists a bias that male players are far superior. China’s Hou Yifan is ranked 83rd globally. She is the highest ranked female among all professional chess players. The highest ranked male (number one in the world) is Norway’s Magnus Carlsen. Like in professional basketball, most fans of chess know and idolize Carlsen. They’re less likely to do the same for Yifan, considering there are 82 chess players ahead of her. All male.

But according to NYU Professor Wei Ji Ma in his piece titled, “What gender gap in chess?”:

…there is no evidence that the “achievement gap” is anything but a participation gap. Statistically, there is nothing to suggest that top female players are underperforming given the overall ratio of female to male players. In fact, taking into account the systemic injustices and biases that they had to overcome to get where they are, they are likely over-performing.

The same is true for the WNBA. As we’ve demonstrated in Part I, there are some women — in some stat categories from our dataset — who outperform their male counterparts despite the participation gap (there are 3x more NBA players than WNBA players).

So while men and women have different physical builds, there is evidence that perceived differences in athleticism are due to systemic differences. For example, a WNBA basketball rim is 10ft off the ground, which is the same as in the NBA. Men can throw windmills and alley oops all game long on a 10ft basket. Women can’t because the WNBA was fundamentally designed around a men’s game (something that goes ignored by dozens of YouTube videos mocking the Candace Parker and Brittney Griner dunks). Some of the best female basketball players in the world are trying to change this.

Many fans — myself included — perceive a difference in talent, but what they’re really seeing is a participation gap and a game designed around male physicality. There’s plenty of literature (just one example here) that proves this theme goes well beyond basketball.

For these reasons, WNBA teams found different ways to win. As I’ll demonstrate in Part III, their drastically different style and approach means more parity, more equitable distribution of the ball, and a style of play worth celebrating.

Let’s place systemic bias aside (very briefly). If a female league and a male league had the same inaugural season, would one receive more cash up front? Is there bias in initial investment?

Unfortunately, few financial figures are publicly available. But consider this: the WNBA’s inaugural season was in 1997. There are leagues in the above dataset that have been around for about as long, or are even newer, that already make exponentially more despite, in some cases, having nominal differences in viewership (I understand viewership is not representative of all revenue — lest we forget ticket and merchandise sales, licensing, broadcasting deals, etc — but it’s a good gauge for interest).

Take the MLS. It’s been around only 4 more years than the WNBA. Yet the average soccer player’s salary is $345,000. The MLS’s revenue is nearly 2000% higher than the WNBA’s as of 2019, despite a nominal average per game viewership difference of 8% (268,000 vs 246,000).

And eSports’ most notable property, Overwatch League, was started in 2016. And while only 6% of revenues go to their players (versus 17% in the WNBA), the average player makes $114,000, or $39,000 more per year than the average WNBA player. It’s also worth noting that the average Overwatch player is 5 years younger than the average WNBA player, 22 versus 27.

The number of viewers a league has helps to gauge audience interest. Corporate sponsorships help to gauge financial interest.

According to the LA Times, “for every dollar that corporate America spends on sports sponsorship, less than a penny goes to women’s professional sports. The WNBA in particular gets a fraction of that fraction.”

These corporations broker deals with each team. These sponsorship, licensing, and broadcast deals then go through each team’s front office. It’s worth noting that these front offices are made up mostly of men.

In Phoenix, Minnesota, Los Angeles, Dallas, Washington, New York, and Indiana, where there are NBA and WNBA teams, both teams are owned by the same person. For example, Ted Leonis owns both the Washington Wizards and the Washington Mystics.

Every single owner is a man. Save for the Atlanta Dream, the Seattle Storm and half of Chicago Sky, the remaining teams are owned by male-dominated gambling firms (93% of American fortune 1000 leadership is comprised of men). There’s an undeniable representation issue here that, unfortunately, won’t surprise many readers.

It’s interesting to see the rapid growth and financial success of male leagues owned by males, especially in their earlier years like with the MLS and Overwatch. I can’t prove intrinsic partisanship or prejudice — and, again, it’s easy to blame economics — but it’s hard to overlook this trend as a coincidence.

The bias is true among fans too. It’s almost never verbalized, but (largely male) sports fans will shyly think, “it’s less entertaining” or “men are just better athletes.” Frankly, I’m guilty of this. Until writing this piece, I hadn’t taken even an ounce of interest in women’s basketball. But as I’ll explain in Part III, this intrinsic bias that likely exists can be reshaped if you focus on what makes the WNBA great, rather than comparing it to the NBA.

writer / creative director/ data scientist / corrupt politician /

writer / creative director/ data scientist / corrupt politician /