Michael Peterson’s work helped turn the Tampa Bay Lightning into a Stanley Cup finalist.
As an undergraduate and graduate student at Texas Tech University, hockey was about the furthest thing from Michael Peterson's mind, both as a sports fan and when considering how to combine his love of sports and career plans.
Turns out, though, Peterson might just end up being a pioneer in the sport.
As the Tampa Bay Lightning open the 2015 Stanley Cup playoffs Wednesday (June 3) against the Chicago Blackhawks, Peterson will see the hard work he and the rest of the organization put into producing a team just four wins away from capturing one of the most coveted prizes in sports. He'll also be able to see how a growing trend of statistical analytics in hockey helped put together this year's club.
“It's difficult to say how much I played a part in it because there's a lot of people who all provided their input,” said Peterson, who earned dual bachelor's degrees in Mathematics and Computer Science from Texas Tech in 2005 and his master's degree in Mathematics 2007. “Scouts, management, coaches, player development, that all goes into it. I can't say how much I specifically contributed, but I definitely provided my input as much as I've been able to do in my position. That's what analytics can provide and that has developed over the years.”
Call it the Moneypuck, in essence the Moneyball of hockey. While it is commonly known and used in baseball, it is still in its infancy in hockey, and when all is said and done, Peterson could become the father of statistical analysis in hockey personnel decisions.
Peterson has always been a big sports fan, and in his time at Texas Tech tried to mesh his love of sports and statistical analysis. He was a regular at Red Raider baseball games and for a short time used analytics to help the football program. Baseball, however, was always his favorite sport, and no other sport lends itself more to the use of statistical analysis.
No other sport lends itself to the use of statistical analysis like baseball, Peterson's favorite sport.
“I learned a lot through my computer science classes that taught me a lot about programming and coding that I use on a daily basis now as far as retrieving statistics,” Peterson said. “Also, my time in the math department working with Dr. Chris Monico as an adviser, I enjoyed working with math. Everything grew my interest in it.”
Peterson left Texas Tech to pursue an MBA at the University of Central Florida, and while there he did some consulting work for the Cleveland Indians and Tampa Bay Rays. But it was an internship that set his career course on the fast track.
That internship was with the Lightning, who was looking for someone to do statistical analysis. But, Peterson said, it was an open-ended internship in terms of looking for someone who had fresh ideas about approaching the game, inspired partly by what former Oakland Athletics general manager Billy Beane had created, a movement that became Moneyball.
After completing the internship, Lightning administrators approached Peterson about his vision for a full-time statistical analysis position. After giving them his vision for the position, he was hired on a full-time basis. He said at the time only one other team had someone performing any type of statistical analysis, but that person was more of a scout, making him, essentially, a pioneer in his sport.
“It was basically, ‘what can you do, how can you help us, what ideas or new ways and approaches of looking at things do you have?'” Peterson said. “It was very forward-thinking for an organization to be that open-minded. Other organizations today still don't want anything to do with it and see no value in it. The Lightning were very forward-thinking at the time, now six years ago, to have this vision.”
New Way of Thinking
Not only is statistical analysis still in its infant stage in hockey, but using the method to evaluate players and performance takes a whole new approach.
In baseball, evaluating performance is easy. Batter vs. pitcher. Batter vs. defense. Even though there are nine players on the field, baseball is a 1-on-1 oriented sport.
Hockey, on the other hand, is more of a fluid sport where it's 5-on-5 for most of the time with thousands of possible outcomes, Peterson said.
“It's difficult to draw direct parallels between the sports,” Peterson said. “It is essentially starting over, starting from the ground up and trying to piece together certain events or situations and see how they interact with each other. Everything depends on who you're playing with and who you're playing against.
“If you take a guy and put him on another team and you don't know who his teammates are, you can still anticipate what you will get from a player in baseball. In hockey, you do that, you just don't know. It depends on who gets you the puck or who receives the puck or who is the playmaker.”
Slowly, but surely, the use of statistical analysis in hockey is growing. Peterson said last summer six or seven teams hired statistical analysts, and the Toronto Maple Leafs have a whole department dedicated to it.
“Last year in the hockey analytics community it was kind of the summer of analytics,” Peterson said. “Last summer it grew, but I would say there are still maybe a third to half of the league that don't have anyone in that type of position. Over the next several years, every team will have one at some point. Teams are investing resources and money into it.”
Depending on the success of the Lightning over the next two weeks, that push toward statistical analysis could be accelerated. And when it becomes widespread over the sport, a Texas Tech graduate will be one of its pioneers.
“I just wanted to try to explore new areas,” Peterson said. “It's been exciting to be a part of that and we'll continue to investigate new areas.”