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 sophisticated 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 noncompete 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 knowledge 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.

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前台免费机构：数据分析和非竞争协议如何破坏美国职业体育联盟的竞争平衡

美国职业运动队越来越依赖复杂的数据分析形式来确定潜在的竞争优势领域。确实，越来越多的证据表明，该领域中最先进的团队正在利用他们从数据分析中获得的见解，为自己在比赛中的竞争提供持久的，可观的收益。同时，体育特许经营经常利用非竞争协议来保护其数据分析所产生的专有信息。不幸的是，最近的一项学术研究表明，这种依赖契约不竞争的做法会降低行业内的知识传播速度，从而使团队难以赶上数据分析的早期采用者。因此，球队越来越依赖数据分析，以及使用不竞争协议来保护其发现的结果，对联盟努力在其特许经营中维持适当水平的竞争平衡可能产生重大影响，但迄今为止尚未得到人们的认可。本文探讨了这种情况，及其对美国职业体育联盟治理的影响。