Nassim Taleb’s 2007 book, The Black Swan, was influential in changing the way we think about predictive models and unpredictable events. Now, the ever-brilliant folks at FanGraphs have taken Taleb’s paradigms and applied them to Major League Baseball’s first-year player draft.
The matter of drafting baseball players may seem trivial in comparison to Taleb’s focus on global financial markets, but baseball is big business, and teams are always looking for innovations that will set them apart from the pack. Even for professional scouts, the draft is a pretty daunting challenge. They’re asked to look at a pool of thousands of 17- to 22-year-old players, and pick the select few who have the combination of physical talent, intelligence, and injury resistance needed to sustain long careers at baseball’s highest level. The odds are against them; the probability that a drafted player will appear in even a single MLB game is about one in six. The rest are destined for careers in the minor leagues. Finding just one extra MLB-caliber player has the potential to turn a team’s fortunes around.
The Black Swan asks the reader to imagine two worlds: Extremistan and Mediocristan. In Extremistan, improbable events are particularly influential, and can completely throw off predictive models.
“Imagine how [the average wealth in a room] changes after Bill Gates walks in. It’s an unforeseeable, longest of longshots that Gates is the random person who walks in, but that fact changes the whole game: Gates accounts for almost all of the wealth in the room. Taleb also mention how book sales in a room full of authors might be affected if J.K. Rowling enters,” writes FanGraphs’ Kiley McDaniel, describing Taleb’s concept of Extremistan.
In Mediocristan, a single event is unable to significantly alter the big picture. Bill Gates’ sudden arrival may have an enormous impact on the average wealth of a room, but if you were asked to average out the resting heartbeat of everyone present, almost anyone else would have the same negligible impact as Gates.
McDaniel posits that the early rounds of the MLB draft resemble Extremistan, while the later rounds are more like Mediocristan. His premises, analyses, and conclusions are much too complex to be summarized briefly, but they are must-read material for those interested in the confluence of sports and Big Data. While the trend is hardly new, it’s exciting to see the sports world become increasingly reliant on advanced analytics, and less complacent in accepting conventional wisdom. The application of Taleb’s theories can only add to the enlightenment that sports-oriented analytics have to offer.