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Description

In this episode, Adam Grossman sits down with Max Mitchell, a Northwestern MSA graduate student and teaching assistant, to unpack the findings from Max’s thesis research (and accompanying article) on NIL, the transfer portal, and player movement in college football. Using a novel, data-driven approach, Max challenges the popular narrative that NIL and transfers are chaotic and unsystematic. Instead, the data suggests something far more familiar: athletes are making rational, incentive-based decisions that closely resemble traditional labor market behavior.

Max walks through how his research journey began with a simple observation during a Clemson–Florida State game—and evolved into a multi-year project involving tens of thousands of recruits, thousands of transfers, and hundreds of hours of data cleaning, matching, and modeling. Along the way, he explains how structural barriers before college shape player outcomes, why transfer behavior changed so dramatically after 2018 and 2021, and how NIL fundamentally altered the incentives facing college athletes.

The conversation dives deep into what motivates players to transfer, why “upward” and “downward” transfers optimize for different outcomes, and how athletes balance short-term playing time with long-term professional upside. Perhaps most notably, Max shares a striking finding: NIL valuations are now a stronger predictor of NFL participation than high school star ratings—suggesting that dynamic, market-based signals may outperform static recruiting metrics when it comes to forecasting success.

The episode also explores what this means for programs, conferences, and the future of college football. From NIL spend correlating with wins, to roster mobility increasing as financial incentives grow, the discussion reframes NIL not as chaos—but as a market finding its structure in real time.

Whether you’re a student of sports analytics, a college athletics administrator, or just trying to understand how NIL is reshaping the game, this episode offers a rare, data-backed look at what’s really happening beneath the headlines.