The 2003 book Moneyball marked a statistical revolution in the game of baseball, yet accounted for just 10 terabytes of data in a year’s worth of games, with most of that coming from detailed data of every pitch and swing. Just over 10 years later, everything is tracked and almost the same amount of real-time data is generated in a single game, with an astounding 1.5 petabytes of structured and unstructured data amassed every year, ushering in a second, even greater baseball renaissance.
In this Knowledge Sharing article, recognized in the Elite category in the 2014 Knowledge Sharing competition, author Bruce Yellin examines the influence Big Data has on the modern game of baseball, a sport where statistics have thrived from the Industrial Age to the Information Age. Bruce provides new and insightful information on how baseball players, coaches, managers, and management use predictive analytics to gain a competitive edge over their opponents. Big Data topics such as analytics, clustering, stratification, and others are illustrated as they apply to players, managers, team ownership, media, and the multitude of fans who avidly follow this sport in many parts of the world.
Those familiar with Bruce’s previous Knowledge Sharing articles will recognize his entertaining and informative writing style as he details a blow-by-blow, yet fictional baseball game to show how big data helps teams craft management decisions, create strategic game plans, and make tactical player adjustments. Bruce also discusses how ballplayers leverage these analytics and how umpire’s calls threaten carefully laid battle plans. Through this, the reader will come to understand and appreciate big data charts, diagrams, and photos of how the game is really played, and just what the next few years will bring. Along the way, readers learn about the role Hadoop is playing, see big data-driven smart apps in action, and even get to examine individual pitcher data records to see how it is done.