Get down and nerdy: why analytics matter

It is difficult to contest the recent success of analytics in American Sports. This is true particularly in the way analytics have allowed teams to better evaluate talent and uncover players that are skilled but off the radar, leading to cheaper and more efficient contracts. In the last decade, sport analytics have infiltrated nearly every professional sports league in a multitude of ways. This is especially true for Major League Baseball where nearly every team employs a full-time sabremetrics analyst. This trend proves that when it comes to any type of competitive advantage, jocks are not afraid to get nerdy.

But analytics’ recent rise to prominence didn’t stop TNT’s basketball commentator and NBA Hall of Famer, Charles Barkley, from denouncing sports data on TNT’s studio show “Inside the NBA” early last month. Barkley called out the Houston Rockets’ General Manager Daryl Morey, a champion of data analysis. Barkley stated that he “always believed analytics was crap,” and that those who practice it are just a “bunch of guys who have never played the game, and they never got the girls in high school.” Barkley’s comments were extremely short sited considering that analytics are so much a part of modern professional sports. Paradoxically, they are easily overlooked.

Last weekend, the ninth annual Sports Analytics Conference at the Sloan Business School at MIT crushed the validity of Barkley’s comments and proved that analytics are a viable and essential strategy in modern sports. Speakers ranging from the commissioner of the NBA Adam Silver to Harvard geography professor turned NBA data wizard Kirk Goldsberry made up a diverse coalition of innovators meeting at the intersection of sports and science. The conference resembled an All Star sporting event. Yet it was for sports management and media instead of players. MIT Sloan 2015 combined the excitement of a sold-out game with the research and intellect of a true academic convention.

The conference’s intellectual side was displayed prominently during the award segment when the Alpha Award for best research paper on sports analytics and a $15,000 prize was split between “Who is Responsible for a Called Strike” and “Counterpoints: Advanced Defense Metrics for NBA Basketball.”

The first paper, written by Joe Rosales and Scott Spratt of Baseball Info Solutions, utilized computerized strike zone film from the past MLB season in order to create a system to analyze the ability of MLB catchers to influence umpires’ pitch calls. The other winner, created by Harvard academics Kirk Goldsberry, Alexander Franks and Andrew Miller, ventured into a new frontier of NBA statistical analysis and created measurements that calculated players’ defensive ability. Both papers were well written and researched, furthering the discipline of sports analytics and creating new perspectives to study.

The research presented from the Harvard delegation was particularly fascinating in the way it created a format for defensive play to be evaluated at the NBA level. “Counterpoints: Advanced Defense Metrics for NBA Basketball” represents groundbreaking progress considering how much of basketball stats focus on offensive achievement that hosts a myriad of measurements while defense has traditionally been restricted to steals and blocked shots.

Depending heavily on player tracking technology the NBA implemented for the 2013-2014 season, the study examined defensive matchups between individual players to calculate counterpoints. Counterpoints measure the defensive efficiency of a single player that is collected by comparing how many points a player allows for every 100 points they score.

Yet what might be the most enlightening aspect of the paper is the defensive data displayed on a shot chart that reveals how a certain player’s defensive skills influence how accurately, frequently and from where his opponent shoots on the basketball court. The shot charts highlight sports analytics’ ability to display complex trends and in this case, the charts reveal how a player’s defensive skills interact in a team’s scheme. The charts show tall players like Dwight Howard and Tim Duncan allowing mid range and three point shots while expertly defending the interior and bringing their opponents’ close range efficiency way down. The conference presented a thought provoking counter to the success of analytics in sports with former Miami Heat small forward Shane Battier’s interview and explanation of his role in the success of the two-time champion Heat. Battier’s stats were never top notch but that doesn’t mean his role in his teams success should be overlooked. Instead of scoring tons of baskets or catching dozens of rebounds, Battier excelled in areas that the statistician doesn’t record, like using his 6’8” frame to create productive offensive spacing.

According to, during the conference Battier claimed that “the extra foot of space I gave LeBron was critical to him completing the play or not.” His role on the Heat was not as one dimensional as his averages display. Battier’s success stands as an example of where sports analytics falls short in completely encompassing the many complexities of basketball.

Like most things, there is no completely right answer in the fight between sports stats enthusiasts and those who consider analytics to be “crap.” Testimony from former players such as Battier show that stats never show the entire picture but the research presented at MIT’s Sloan Sports Analytics Conferences shows that every year the numbers become stronger, more insightful and more revealing. And in a time when fantasy sports and video games immerse fans in the competitive nature of sports, I don’t predict analytics are going anywhere anytime soon.

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