Big data has a seemingly unlimited number of commercial applications. Just ask the brilliant minds at Rock West Solutions in California and Utah. They are constantly working on projects that reach nearly every sector of the U.S. economy. But is every big data application a worthwhile application?

For instance, take big data in pro sports. It is all the rage these days. Yet hard-core sports purists cannot help but wonder if big data is actually taking the fun out of their favorite pastimes. When everything is data driven, how much of pro sports is really about athletic performance, toughness, and the proverbial battle of the wills?

Big Data in the NFL

Football is undoubtedly the most popular sport in the United States. Just in terms of fan participation and annual revenues, no other professional sport holds a candle to it. At the center of it all is the NFL. And at the center of the NFL these days is an increasing reliance on big data and analytics.

Every year the NFL holds its Big Data Bowl, a competition among data and analytics experts to make the best use of data gathered during weekly games. The goal is to find new and more effective ways of using data to enhance play, improve coaching, and make football more appealing to an ever-wider audience.

It all sounds really great in principle. Yet data and analytics might dampen some of the competitive aspects of sports by taking things like gut instinct and experience out of the equation. Analytics might be creating a watered-down product that loses some of its excitement if, for no other reason, than the fact that everybody knows what is coming.

Big Data in MLB

Major League Baseball (MLB) was one of the earliest adopters of big data and analytics in pro sports. That is no surprise given the amount of information normally collected by statisticians and coaching staffs. MLB has simply taken what teams have been doing for generations and improving it through big data techniques.

A typical major-league catcher doesn’t spend a whole lot of time in the batting cage. Instead, any time not spent talking things over with the pitching staff is spent analyzing stream after stream of data. Catchers study opposing players and their batting tendencies. They study infield and outfield positioning. All of the data they digest is supposed to make them better game managers.

In the dugout, managers and their coaching staffs rely on big data for making in-game decisions. The computer tells them when to make a pitching change or bring in a pinch-hitter. They rely on analytics to determine when to shift the defense or pull their infielders in.

The Maturity of Predictive Analytics

Rock West Solutions explains that what is now happening in pro sports is all about the maturity of predictive analytics. When big data was first born back in the 1990s, no one really knew what to do with all of the data being collected. That has since changed. Analytics is the reason behind the change.

Analytics is, in the simplest possible terms, the ability to draw correlations between different data points in order to extract relevant information. Do it well and you can use data to successfully predict the outcome of just about any event.

Big data and analytics now have a firm hold on pro sports. But are they taking the fun out of the game? Fans will ultimately decide that. In the meantime, they are changing the way pro sports are played and enjoyed.