The Moneyball Playbook

In 2002, the Oakland Athletics went 103-59 with one of the lowest payrolls in baseball. The success inspired Moneyball , which tells the story of GM Billy Beane and how he found value in undervalued players by leveraging data no one else was using. Even most non-baseball fans know Beane through Brad Pitt's portrayal in the film. Only a few, however, know about Theo Epstein and what happened next. Epstein was 28 years old when he became General Manager of the Boston Red Sox. He was an analytics guy, just like Beane, but with one key advantage: the resources of a large-market team. In 2004, he led Boston to its first World Series win in 85 years. Then he did it again in 2007. And in 2016, when the Yankees were still debating how much to lean into the data, Epstein won once more as GM of the Chicago Cubs, ending a 108-year drought, the longest in MLB history. The debate was over. Beane proved the model worked. Epstein proved it scales. I have spent the last several years trying to prove the same thing in residential real estate. First as the head of brokerage at Charney Companies, and increasingly as an advisor to other owners who want to apply the same framework to their own portfolios. And not because the analogy is clever, but because the problem is identical: an industry running on conventional wisdom, comfortable with incomplete data, and largely uninterested in asking whether the things it measures are actually the things that matter.