It’s an exciting time to be an analytics professional in the sports industry. Historically, those who worked in sports analytics were sports enthusiasts who combined their quantitative skills with an application area of intense interest. But, for a growing number of colleagues, working in sports analytics is a viable career option.

Sports analytics got a boost in recent years from the smash hit Moneyball (both the book and the movie). However, in some sports, i.e. baseball, football, and basketball, analytics goes back decades. Newer uses are appearing in soccer, hockey, even NASCAR, as well as a variety of Olympic and recreational sports. Depending on where you draw the line, sports analytics can also include fantasy sports, fitness, and professional online gaming.

We are seeing explosive growth in sports analytics due to an increased interest on the part of owners, managers, coaches, and athletes, combined with data that was previously unavailable. Much of this is due to new systems, like the StatCast system in MLB, SportView cameras in the NBA, and individual biometric physio monitors in nearly every sport.

The opportunities for data-driven decisions are almost limitless. Some of the more common decisions include those that are more operational in nature (player evaluation for recruiting, scouting, and trades; lineup selection and arrangement; in-game strategy using game theory) and also those that are more business oriented (fan and consumer modeling; ticket sales; and even in-venue sales forecasting). After reading through the articles, listening to the podcasts, and watching the videos, you may have some great ideas of your own about how to apply analytics in sports.