Using sports analytics to get ahead in the game

Arguably, no one understands the intersection between sports and analytics better than Kenneth Massey.

The 47-year-old Virginia Tech alumnus developed a college football ratings model that played a large role in determining the two participants in the Bowl Championship Series (BCS) national title game every year for 14 consecutive years from 1999-2013. The Massey Ratings were one of six computer rankings used by the BCS and thrust this mathematics whiz to the forefront of college football conversations every fall.

He became a well-known name among passionate fan bases — many of whom were more than willing to voice their opinions of him and his colleagues.

“We were the villains,” Massey said with a smile. “The bad guys.”

Massey, who earned his master's degree from the Department of Mathematics within the College of Science in 1999, said that to students during a Q&A session in Sierra Merkes’ Introduction to Sports Analytics course held Nov. 3 in one of Hutcheson Hall’s quaint classrooms. The approximately 20 students in the course asked numerous questions of Massey, who told of his career journey and relayed other scholarly advice to a group interested in numbers, analytics, and in the case of many, sports.

The Introduction to Sports Analytics course made its debut this fall. Not to be confused with the major in sports media and analytics, this three-credit course resides within the Department of Statistics in the College of Science. Its curriculum uses sports to introduce students to data and data collection methods, visualization techniques, game performance statistics, inferential statistics, and predictive modeling techniques for sports data.

Taught by Merkes, a former Radford University women’s soccer player who recently earned her doctoral degree in statistics from Virginia Tech, the course serves a precursor to a more advanced Sports Analytics Statistical Research class taught by Paul Sabin ’19, who received his doctoral degree in statistics from Virginia Tech and is well-known in data analytics circles for his work with ESPN.

“We decided to create this class so that we could get more kids into sports analytics and hopefully get them into statistics, so that maybe they declare that as a major,” Merkes said. “We’re hoping that students use this class as a focal point. Statistics is very applied. We can apply it to things we love. For a lot of students, that’s sports.”

Merkes’ course features a blend of students pursuing a variety of majors, many with a common interest – a passion for sports. Yet they can apply the concepts, theories, and approaches they learn in these two sports analytics courses to most fields of study.

Many students dream of pursuing a career in sports analytics with a professional sports team, and certainly analytics affects every part of a sports business. Examples include in-game strategy, social media engagement, and return on investment from merchandise sales and marketing deals. Decisions on these examples revolve around data and numbers.

But the sports job market is extremely competitive, leading Merkes to encourage her students to be flexible with their career aspirations.

“The big question my students are asking is, ‘How do I get into the field of sports analytics?’” Merkes said. “It’s a small industry. To get in there, you need connections. You want to blend your passions, but it’s hard because, for one team, there might be only two or three analysts, depending on the sport. So it’s very hard to get in and be noticed. A lot of it is networking. But the growth for analytics in general is much bigger.”

Massey echoed those sentiments. Despite his name recognition and despite helping a couple of Major League Baseball teams several years ago, he never pursued a career in sports, preferring instead to maintain his Massey Ratings website as a hobby rather than a career. He has even expanded his ratings to sports such as soccer, hockey, volleyball, and handball.

In 2005, he joined the faculty at Carson-Newman University in Jefferson City, Tennessee, and today, he works there as a data analyst while also teaching math courses.

“I would advise students not to intentionally restrict their career path to sports,” Massey said. “Try to get working knowledge of other industries as well and have a general understanding of math and statistics and analytics that you can apply to a variety of problems.

“I do know it’s a pretty competitive field to get a job with a professional team. Some people can do it, and if you think those opportunities are there, then that’s great. Do like I did and start a hobby website where people can find your work, so you have a portfolio that people can see what you’ve done. But the great thing about math is that it can be applied in a lot of different domains.”

Isabella Shaher heard the message. The junior from Centreville, Virginia, is pursuing a degree in computational modeling and data analytics, known more commonly by its acronym CMDA, and dreams of working for her favorite NFL team, the Pittsburgh Steelers.

“That’s a big dream of mine, but more realistically, I’ll probably be a data analyst,” Shaher said. “If it’s for a sports team, that would be fantastic, but if it ends up taking me down another route, like insurance, for example, that would be great as well. Being a CMDA major, everything is generalized, which I think is cool. You get to do a bit of everything. You should always dream big, but realistic.”

Shaher and two of her classmates are having some fun and gaining real-world experience at the same time by working on a project with the Virginia Tech volleyball team, with the goal of helping the team improve. Merkes requires the group to give a presentation to the class toward the end of the semester.

“They’re Division I, and it’s just a big opportunity,” Shaher said. “I was very excited about it.”

While pursuing her doctoral degree, Merkes worked with computer scientists, engineers, and even the Virginia Tech softball team on various projects. That’s a big reason why she half-jokingly insists that every student pursue a degree in statistics or computational modeling and data analytics.

Data drives today’s world, and those with the ability to organize it efficiently and effectively will be in high demand. The Introduction to Sports Analytics and Sports Analytics Statistical Research courses were designed in part to help meet that demand.

“You get to play in everyone’s area, and I think that is so cool,” Merkes said. “I just want to keep exposing that to the students. Whatever your passion is, I promise you somehow stats is related. You have to analyze data, forecast, understand how the data is working, and if I can get students to realize that stats is important, and it applies to all these different fields, then I’m doing my job and hopefully more kids will come to our classes.”