Brooks Koepka and the Human Element to Quantitative Models

Koepka’s ability to dominate majors is a lesson to quantitative analysts.

Perhaps the most widely known contribution of sports analytics was documented in the 2003 book, Moneyball. In the book, Michael Lewis illustrates how an edge in data analysis can make up for millions of dollars spent in salary cap. This lesson extends to businesses, other sports, and governing decisions — and 16 years later not everyone has caught up.

On the other hand, there are limits to edges in data analysis. It didn’t take long for other baseball teams, probably due to the high stakes nature of their decision making, to implement the lessons of Moneyball. Ultimately everyone has access to a similar set of data, and the edges between one team’s data analysts and another grew smaller and smaller.

Where does Brooks Koepka come into all of this? I think he offers a great example of how using non-quantitative information can factor into quantitative models. If you’re a golf fan, you’re aware of his major track record in the past few years. He’s had 4 major wins, and even the majors he doesn’t win, he finishes strong. When you dive into the numbers, it gets more absurd. Among active players, only Tiger and Phil Mickelson have more majors (15 and 5 respectively). Rory McIlroy, like…

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