From its initial release, Travis Sawchik’s book “Big Data Baseball,” was immediately compared to Moneyball and has been affectionately referred to as “Moneyball 2.0.” Big Data Baseball has even been referred to as “Moneyball on steroids” by its publisher. While it may not quite be Moneyball, it is something in a similar vein and a book deserving of all its praise. The book details the Pittsburgh Pirates organization and their rise from mediocrity to their first playoff appearance in 20 years in 2013. The book focuses more in-depth on the Pirates organizational structure, from General Manager Samuel Huntington, to Coach Clint Hurdle, all the way down to many of Hurdle’s assistants and even quite a few minor league coaches in the Pirates organization. It is a top down evaluation of the Pirates 2013 success story and how they went from 20 years of losing to a playoff appearance simply through more in-depth use of various sabermetrics evaluations including defensive shifts, pitch framing/catcher defense, and pitch use.
The book has generated all sorts of buzz in the sabermetrics community and definitely lives up to all the hype that has accompanied it. While Moneyball was a bit of a revolution for its time, “Big Data Baseball” holds a somewhat similar appeal. As in Moneyball, this is the story of a franchise strapped for money needing to do anything in its power to put a winning team on the field after years of mediocrity and a fed up fanbase. While the focus for the Athletics was something as simple as a more widespread use of On Base Percentage, the focus for the Pirates was on more advanced metrics that have grown in importance in recent years. Defensive shifts, pitch framing, pitch selection are all the buzzwords of “Big Data Baseball.”
On top of the sabermetrics involved in the Pirates success story there is also quite a bit on several players and how simple statistical evaluations were able to fix what were considered “broken players.” There’s the story of Russell Martin who didn’t garner much attention from any other team but was the focus of the Pirates offseason because of his great pitch framing numbers. Or the stories of AJ Burnett and Francisco Liriano who seemed to both be on their way out of baseball before tweaks to their pitch locations made them All Stars once more. And finally the story of Starling Marte and how the Pirates found him while scouting in Cuba and signed him before anyone else released the kind of player he could be. The book is filled with brilliant coaches, brilliant strategies, and many player success stories thanks to the use of sabermetrics from the very top of the organization all the way on to the field.
“Big Data Baseball” is an intriguing book that eloquently tells the story of the Pirates recent success. It presents a model that can be duplicated by other teams and is a model of the success of sabermetrics league wide. As revolutionary as Moneyball was for its time, “Big Data Baseball” has taken the baseball sabermetrics revolution to a whole new level. It really goes to show how far baseball as a sport has come in such a short time and where it can go in the future. Travis Sawchik seamlessly tells this story and weaves it into it’s place in baseball history. It’s safe to say “Big Data Baseball” is a must read for anyone with an interest in sabermetrics and big data or even just the casual baseball fan. “Big Data Baseball” is the next revolution to the game of baseball and it seems like the revolution is here to stay.