Former NBA Analytics Executive Says Sports Data Revolution Still Undervalued as League Grapples With Tanking Crisis
Ben Alamar, who spent years building analytics operations for the Oklahoma City Thunder and Cleveland Cavaliers, believes the sports data revolution deserves more institutional recognition—even as the NBA confronts fundamental questions about how teams use that same data to game the system.
In a February 18 podcast with Wharton faculty members Cade Massey, Eric Bradlow, and Adi Wyner, Alamar argued that pioneering work in sports analytics warrants Hall of Fame consideration, while simultaneously addressing how data-driven decision-making has intensified debates over tanking and draft reform. The conversation, published by Wharton's Knowledge platform, comes as finance leaders increasingly look to sports franchises as laboratories for data-driven organizational strategy.
The timing is notable. Professional sports teams have become case studies for CFOs and finance executives exploring how to operationalize analytics—turning raw data into competitive advantage without destroying the underlying business model. The NBA's current struggle with tanking incentives illustrates the challenge: teams now use sophisticated analytics to determine when losing games strategically improves long-term championship odds, creating a prisoner's dilemma that threatens fan engagement and league integrity.
Alamar, who also authored "Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers," discussed how the league's draft system creates perverse incentives that analytics have made impossible to ignore. When data clearly shows that accumulating high draft picks through poor regular-season performance offers the highest expected value path to future success, teams face a fiduciary duty to shareholders that conflicts with competitive integrity.
The broader question for finance leaders: how do you build a data-driven culture that optimizes for the right outcomes? The NBA's experience suggests that measurement systems shape behavior in ways that aren't always desirable. If your KPIs reward short-term underperformance for long-term gain, don't be surprised when rational actors optimize accordingly.
Alamar's call for Hall of Fame recognition for analytics pioneers reflects a larger debate about how organizations value innovation in decision-making infrastructure. Sports franchises were among the first to systematically replace intuition-based management with quantitative frameworks—a transformation now playing out across corporate finance departments.
The podcast, which runs over an hour, also touched on the future of team building in an era where every franchise has access to similar analytical tools. The competitive advantage, Alamar suggested, increasingly comes not from having better data but from organizational willingness to act on insights that contradict conventional wisdom—a lesson that resonates beyond the basketball court.
For CFOs watching the AI transformation of their own functions, the NBA's analytics journey offers a preview: powerful tools that create new strategic options, unintended consequences that require governance frameworks, and the persistent challenge of aligning incentives with desired outcomes. The league's ongoing struggle with draft reform and tanking suggests that even mature analytics operations must continuously revisit whether they're measuring—and rewarding—the right things.
The conversation is available through Wharton's Knowledge platform, part of the school's ongoing coverage of how data analytics reshapes competitive strategy across industries.
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