While the MIT Sloan Sports Analytics Conference is ostensibly an academic enterprise, this year’s conference was the first to feature an entire panel devoted to teaching sports analytics.
The panel, From the Classroom to the Locker Room: Teaching the Next Generation of Sports Analysts, featured a collection of college educators — Jeremy Abramson from the University of Southern California, Jeff Ohlmann from the University of Iowa, Ed Kaplan from the Yale University, Mike Magazine from the University of Cincinnati, and Nils Rudi from INSEAD. All teach (or in Rudi’s case, will teach next semester) college classes either completely focused on sports analytics or which incorporate sports analytics to help teach other concepts.
The analytics revolution has taken hold on basketball courts and in front offices around the league. But turning a revolution into an establishment requires money, resources and personnel. All of those things abound in the world of sports analytics but they’re pushed almost exclusively in the direction of things that will improve the product on the floor and the bottom line of the team or organization.
While the knowledge, and search for knowledge, has swept like wildfire through the NBA landscape, the infrastructure to train and prepare the quantity of talented people to maintain it has crept behind at a snail’s pace. Dedicated classes on sports analytics are few and far between. A complete college program solely devoted to sports analytics is still just theoretical. Very little has been done to turn sports analytics into something inherently self-sustaining. The whole ball of wax is currently resting on the enthusiasm of participants their willingness to pull self-educate to a significant degree, pulling together from different sources all the intellectual and creative tool they’ll need.
The professors on this panel are interested training the next generation of sports quants, but there are significant challenges in a field that requires pulling together a disparate collection of skills, often housed in different academic departments. Even figuring out exactly what to teach can be an incredibly complex question, as Kaplan pointed out.
“Are we teaching statistics, or are we teaching modeling, or are we teaching data?”
As analytics has taken a hold on professional sports it has often been pushed forward by individuals trained in other fields, manipulating their professional knowledge to explore a passionate hobby. Conferences like this are called, bringing together interested parties and allowing them to pitch themselves and their various unique skill sets as potential solutions to analytic problems. While this has bred creativity and made space for a huge variety of angles and approaches it often leaves open the question of what qualifications are necessary and how to ensure that people have them.
“Teams and media companies hire people who really know statistics and just enough sports to be dangerous, or people who really know sports and just enough statistics to be dangerous,” said Abramson.
Educators turning their full attention to sports analytics, training an army of talented and comprehensively skilled individuals resolves concerns for professional sports. But the implications of this idea stretches far beyond the court, front office and college classroom. Universities are finding that sports are a wonderful access point for engaging students, but there’s no reason it need to start at such an advanced level.
There is a revolution happening in American public education and it’s built around the Common Core Standards. These standards, for kindergarten through twelfth grade, were developed in collaboration with a variety of professionals in different disciplines and have now been adopted by 46 states around the country. Different states are in different stages of implementation, but in the near future the Common Core standards will represent the educational paradigm for the vast majority of our country.
The Common Core is meant to both standardize the education received by students around the country and to refocus that educational experience on developing the types of skills that students will need to be productive participants in our modern society. American students increasingly struggle with both basic reading and math skills, and of course the higher level cognitive tasks that follow. This recalibration of the Common Core includes an emphasis on problem solving, critical thinking, modeling and research — exactly the kind of foundational skills necessary to work in sports analytics.
Even the professors on this panel have found that using sports to teach concepts and skills with applications beyond athletic evaluation has tremendous potential.
“Sports is a very good setting for teaching modeling and analytics,” said Rudi.
But even in elementary, middle and high school classrooms sports and sports statistics can act as vehicle for drawing students into the exact sort of activities that the Common Core Standards are demanding. This is not just using a basketball player’s makes and misses to teach about percentages. This is about showing students strategies for problems solving, using actual statistics which have solved actual problems. Sport are a relatively controlled environment with well defined rules and a wealth of publicly available numbers to play with.
Per-36 minute basketball statistics are a relatively simple concept, something readily understandable to most middle school students. But they are also a carefully constructed modeling step, allowing for the comparison of different players while controlling for the fact that they may be on the court for different amounts of time. What we consider a relatively basic stat could be used illustrate the idea of controlling variables in a comparison or experiment.
Making sports analytics an (appropriately-sized) piece of the curriculum for students of all ages has the potential to create huge benefits. Imagine what Abramson and Ohlmann, and academics in all sorts of science and math disciplines, could accomplish with students who had already spent years working, not just with statistics specific to that field, but on using, manipulating and controlling those statistics to solve problems, answer questions and find new ones.
Even for those who aren’t interested in a career in sports analytics, an interest in sport can be a doorway to a conceptual skill set that opens hundreds of doors down the road. The benefits of sports analytics can run deeper then refining the Miami Heat’s offense and fairly valuing the statistical contributions of Monta Ellis. It can help house and promote the basic tools of math and science education. Now that’s a revolution worth fighting for.