Free Agency for the Front Office: How Data Analytics and Noncompete Agreements Threaten to Disrupt Competitive Balance in U.S. Professional Sports Leagues

• Published date: 01 March 2021
• Author: Nathaniel Grow
• Date: 01 March 2021
• DOI: http://doi.org/10.1111/ablj.12180

American Business Law Journal

Volume 58, Issue 1, 121–162, Spring 2021

Free Agency for the Front Office:

How Data Analytics and Noncompete

Agreements Threaten to Disrupt

Competitive Balance in

U.S. Professional Sports Leagues

Nathaniel Grow*

U.S. professional sports teams are increasingly relying on sophisticated forms

of data analysis to identify potential areas of competitive advantage over

their league rivals. Indeed, emerging evidence suggests that the most sophis-

ticated teams in this area are using the insights that they derive from data

analytics to establish durable and significant gains over their competition on

the playing field. At the same time, sports franchises frequently utilize non-

compete agreements to protect the resulting, proprietary information that

their data analysis yields. Unfortunately, recent academic research suggests

that this reliance on covenants not to compete can decrease the rate of knowl-

edge diffusion within an industry, making it more difficult for teams to catch

up to early adopters of data analytics. Thus, teams’growing reliance on data

analytics—and their use of noncompete agreements to protect their resulting

findings—could have significant, but heretofore unrecognized, ramifications

for league efforts to maintain an adequate level of competitive balance

amongst their franchises. This article explores this state of affairs, as well as

the implications it presents for the governance of U.S. professional sports

leagues.

*Associate Professor of Business Law & Ethics,Indiana University (Bloomington).

©2021 The Author

American Business Law Journal ©2021 Academy of Legal Studies in Business

121

INTRODUCTION

Teams in the four major U.S. professional sports leagues face something

of a rather unusual existential paradox.

1

On the one hand, teams vigor-

ously compete with their rivals on the playing field in the hopes of annu-

ally winning their league championship.

2

On the other hand, if one team

in the league were to become too successful—to the point that it could

predictably be expected to win on a highly consistent basis—then fans

may begin to lose interest in the sport, threatening the profitability (and

ultimately the viability) of the league as a whole, to the team’s own detri-

ment.

3

As a result, professional sports franchises recognize that they

must, at times, subjugate their own competitive instincts to some extent

in order to help enhance the overall level of competitive balance

within—and thus, the overall profitability of—their league.

4

U.S. professional sports leagues have traditionally attempted to main-

tain a sufficient level of competitive balance amongst their franchises by

implementing measures intended to help equalize the level of playing

talent spread across the league’s teams (including measures such as sal-

ary caps and player drafts).

5

In recent years, however, a new challenge to

the leagues’efforts to maintain parity has emerged: data analytics.

1

For purposes of this article, the four major sports leagues are the National FootballL eague

(NFL), National Basketball Association (NBA), National Hockey League (NHL), and Major

League Baseball (MLB). See Marc Edelman & Elizabeth Masterson, Could the New Women’s

Professional Soccer League Survive in America? How Adopting A Traditional Legal Structure May

Save More Than Just a Game, 19 Seton Hall J. Sports & Ent. L. 283, 294 (2009) (explaining

that the United States’“four premier men’s sports leagues”are the NFL, NBA, NHL,

and MLB).

2

See David L. Anderson, Note: The Sports Broadcasting Act: Calling It What It Is—Special Inter-

est Legislation, 17 Hastings Comm. & Ent L.J. 945, 948 (1995) (stating that “it is vital that

[professional sports] teams compete vigorously on the field”).

3

See James T. McKeown, The Economics of Competitive Balance: Sports Antitrust Claims After

American Needle, 21 Marq. Sports L. Rev. 517, 522 (2011) (acknowledging the challenge that

sports leagues face in finding an acceptable level of competitive balance for fans).

4

Cf. Cyntrice Thomas, Thomas Baker III & Kevin Byon, The Treatment of Non-Team Sports

Under Section One of the Sherman Act, 12 Va. Sports & Ent. L.J. 296, 301 (2013) (observing

that “teams within leagues compete against each other on the field, but they must cooperate

off the field/pitch/court/ice to make the product”).

5

See infra notes 153–155 and accompanying text (discussing the mechanisms commonly

used by sports leagues to maintain adequate competitive balance).

122 Vol. 58 / American Business Law Journal

Professional sports teams are currently awash in data, with franchises

tracking everything from their players’every movement on the playing

field to their sleep patterns and hormone levels off of it.

6

In order to

most effectively harness and exploit this data, teams are employing

legions of data analysts, hiring the likes of “NASA engineers, data scien-

tists from leading statistical software companies, and PhDs in cognitive

neuroscience, applied statistics, and machine learning,”to help identify

any potential insight that could be exploited to give the team a leg up on

its competition on the playing field.

7

As with businesses in any other industry, sports teams use a variety of

mechanisms to protect the resulting intellectual property they derive

from their data analysis.

8

One particularly common—but potentially

worrisome—protective measure that sports franchises frequently adopt is

the practice of requiring their front-office personnel and data analysts to

sign noncompete agreements.

9

Indeed, by preventing their employees

from working for rival organizations for a year or more after departing,

sports franchises can help deter their former employees from disclosing

any valuable proprietary information to their competitors.

10

Unfortunately, this reliance on covenants not to compete has poten-

tially significant, but heretofore unrecognized, ramifications for the

6

See infra notes 20–21 and accompanying text (discussing teams’data collection efforts). See

also Matthew J. Parlow, In Pursuit of Competitive Balance or Payroll Relief?, 9 Ariz. St. Sports &

Ent. L.J. 58, 89 (2020) (stating that “[a]lmost every team in the NFL, NBA, and MLB have

analytics departments that track and analyze data—offensive and defensive statistics—that

help inform player usage and roster decision-making”).

7

Brette Trost, Note, Using the Economic Espionage Act to Protect Trade Secrets in Baseball,

8 NYU J. Intell. Prop. & Ent. L. 128, 130 (2018).

8

See infra notes 78–84 and accompanying text (presenting data regarding the protective

measures that teams are using in this area).

9

See infra notes 83–87 and accompanying text (discussing the use and scope of noncompete

agreements within the sports industry). But see infra notes 172–74 and accompanying text

(noting the circumstances under which teams sometimes waive their rights under these cov-

enants not to compete).

10

See Lara Grow & Nathaniel Grow, Protecting Big Data in the Big Leagues: Trade Secrets in Pro-

fessional Sports, 74 Wash. & Lee L. Rev. 1567, 1588 (2017) (explaining that noncompetes

allow employers to “impos[e] restrictions on a departing employee’s ability to work in a par-

ticular field and/or location for a certain time period … all but ensur[ing] that the former

employee will not have an opportunity to utilize or disclose any of [the employer’s] trade

secrets”).

2021 / Free Agency 123