NBA Analytics Pioneer Says Sports Data Revolution Still Lacks Executive Recognition Despite Proven ROI

NBA Analytics Pioneer Says Sports Data Revolution Still Lacks Executive Recognition Despite Proven ROI

Ben Alamar spent years building analytics departments for the Oklahoma City Thunder and Cleveland Cavaliers, watching data-driven decision-making transform how NBA franchises evaluate talent and allocate payroll. Now, as the author of "Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers," he's making a case that should resonate with every CFO navigating their own AI transformation: the people who built the analytical infrastructure deserve credit for the wins it produces.

Alamar appeared on Wharton's sports analytics podcast on February 18 to discuss NBA trends, tanking incentives, and draft reform alongside professors Cade Massey, Eric Bradlow, and Adi Wyner. But the conversation's through-line was more universal—how organizations struggle to value the architects of their data capabilities even after those capabilities prove indispensable.

The timing is pointed. Corporate finance departments are in year three of their own "Moneyball moment," with CFOs under pressure to demonstrate ROI from AI investments while the analysts building those systems remain largely invisible to boards and compensation committees. Alamar's argument—that analytics pioneers deserve Hall of Fame recognition for changing how teams compete—translates directly to a question finance leaders are asking right now: how do you reward the people who built the machine that's printing money?

The NBA's analytics evolution offers a useful parallel. What began as fringe statistical analysis in the early 2000s now drives decisions worth hundreds of millions in salary cap allocation and draft positioning. Teams that adopted data-driven talent evaluation early—like Alamar's Thunder and Cavaliers—gained measurable competitive advantages. Yet the executives who championed those capabilities rarely receive the same recognition as the coaches and players who benefit from them.

For CFOs, the pattern is familiar. The finance team that built your forecasting model, automated your close process, or implemented your planning platform won't get stage time at the annual meeting. But their work compounds. Alamar's point about Hall of Fame recognition isn't really about basketball—it's about how organizations signal what they value, and whether they're capable of crediting infrastructure builders alongside the people who operate that infrastructure.

The podcast also tackled tanking—the practice of deliberately losing games to improve draft position—and potential reforms to the NBA's draft lottery system. Here again, the corporate finance parallel is obvious: misaligned incentives produce perverse outcomes. When the reward structure encourages short-term underperformance to secure long-term assets, rational actors will game the system. The NBA has tried to fix this with lottery reforms; companies face similar challenges when bonus structures reward the wrong behaviors.

What makes Alamar's perspective valuable is his position as both builder and observer. He's not a consultant selling transformation; he's someone who lived inside the organizational politics of getting executives to trust models over intuition, then watched those models become standard practice. That's the journey most finance organizations are on right now with AI—moving from "interesting experiment" to "how we actually run the business."

The question Alamar raises about recognition matters because it's ultimately about retention and recruitment. If your best analysts watch their work drive measurable business outcomes but see rewards flow elsewhere, they'll leave for organizations that value infrastructure differently. The NBA figured this out slowly; corporate finance is still learning.