Professional sports has been infiltrated with confusing jargon—Usage Rate, Wins Above Replacement, Batting Average on Balls in Play, Win Shares. The glossary goes on for pages. These numbers, commonly known as advanced statistics, are woven into all layers of the sports we love: Ultimate Zone Rating (UZR) in baseball, Player Efficiency Rating (PER) in basketball, Defense-adjusted Value Over Average (DVOA) in football, and Relative Corsi Number in hockey.
Analytics aren’t new to sports, but the trickle-down effect from its use in the front office for roster building to its application for on-field decision making has been gradual. But the top-down pressure is building and coaches are adapting to a new normal in sports. No doubt, television and media producers are making excellent use of the reams of data with every broadcast. Fresh numbers and new angles provide talking points for color commentators and play-by-play announcers as well as fodder for arguments on television and radio sports talk shows. The enjoyment of the game is about what we watch—on the field, court, turf and ice—but the way we evaluate the results is more about the numbers than the performances that generate them. With this evolution comes the need for a new skill set in the sports industry.
The role of data and analytics professional once sat on the periphery of the sports org chart, independent contractors with no access to the coaching staff and a connection to one, maybe two, employees within the front office. But, with analytical-minded professionals overtaking former scouts as leaders across the leagues, data-driven minds now weigh in on important organizational decisions—draft, free agency, player and positional value. These data miners—called sabermetricians in baseball—are valued for their ability to aggregate thousands of data points and mold them into stories that help shape our sports.
Data analytics—the science of examining raw data to draw conclusions—has roots far away from the playing fields. The private sector as well as government organizations have amassed and analyzed data sets for decades, applying IT power to solve business problems. Businesses collect product defect trends to find bottlenecks and resolve pain points in a manufacturing process. Transportation departments study traffic patterns, altering signal timing to ease road congestion. Your study of data analytics doesn’t have to begin in the realm of sports. Educate yourself on business intelligence—data mining, reporting, predictive analysis, general analytics—to make your way into the sports industry. Simply put, learn to demystify the volumes of data that otherwise overwhelm us.
Bachelors and masters programs in Business Intelligence and Big Data Analytics are offered across the country. In Chicago, DePaul’s Information Systems program offers a Business Intelligence concentration teaching students about decision support systems, Web 2.0 tools, data management systems and more. Drexel University’s Master of Science in Business Analytics explores quantitative methods and shows east coast students how to influence decision-making with fact-based insights. A Master of Engineering program at University of California, Berkeley prepares students for data-centric industries with an intense “capstone” project and courses on big data and algorithms. With educational opportunities strewn across the country it’s a matter of finding the right fit. And once you do, harness that knowledge, and the experiences that follow, to make your way as a data analytics professional in sports.
You may enter a front office, likely starting as an intern or part-time employee. Or you could write for one of many data-driven sports websites. And a number of television and radio outlets need data analytical-minded professionals to build out its content. However you choose to apply these skills, you’ll be a member of a field that will take sports into the future.