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Home , Tampa Bay Rays

Data Science is the Future: A Conversation with the Rays

Nikki Shaw Director of Marketing

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Wondering how access to copious Data Science for Dummies Humans amounts of data is changing the As a team member at CoLabs, I hear a lot landscape of professional sports? about data science. It’s a part of who we are, what we believe in, and how we build Let’s get right into it—and let’s software. But somehow it still feels tricky to start big. Everyone (that’s right, define. I looked up a few definitions before I met with Will, and here’s my favorite one. It’s everyone) in today’s developing from Techopedia: world has access to more data “Data science is a broad field that refers to than ever before. the collective processes, theories, concepts, tools and technologies that enable the review, analysis and extraction of valuable knowledge and information from raw data.”

Here, you start to get a sense of how complex Think about it: we wear wristbands that report data science is. But even knowing the what, I on our steps and heart rate. We use television was craving more about the why. “The review, apps that know what genre we like to watch analysis, and extraction” of knowledge wasn’t and keep track of what we’ve seen before. We cutting it for me. So, I asked Will for his take shop on websites that can recommend items right off the bat. we might want to purchase, and some can even notify us when there’s a better price on “If you had to define data science for the something from our list. layman,” I said, “what would you say?” And now, think about it another way—in He looked out toward home plate from his terms of your workweek. You’re likely conference chair and thought for a second. experiencing this data surge no matter your (No, really—the conference room was right industry, too. Maybe you notice it because above left-center field in the , your CRM can track every interaction the Rays’ home stadium.) “At a high level,” he between your sales team and your prospects. said, “I would say data science involves using all Or it could be that your finance team is up to of the information you’ve gathered to help you their ears in spreadsheets when they prep solve problems.” monthly reports. No matter how you slice it, data is everywhere. I knew I’d come to the right place. Even in—especially in!—professional sports. So I sat down with Will Cousins, Senior Data The Road to Tropicana Scientist for the Tampa Bay Rays, to get some insight into how technology and After I’d stopped marveling over our killer mathematics are helping us do more with seats (even on a quiet afternoon with no game the data at our fingertips. going on, the view from the conference room

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was impressive) and Will’s ability to translate prepare yourself. He didn’t flee the room when complex concepts into human terms, we I mentioned the 2011 Brad Pitt movie. In fact, talked a lot about his path to Tropicana. Will he said he appreciated when people have seen majored in math in college at Pepperdine, and it. “When someone mentions ,” he then earned a PhD in Applied Math at North told me, “I know they kind of understand what Carolina State. All along the way, he planned I do.” to be a college professor and researcher. “The research I wanted to do was, in spirit, Great—I was tracking! Next I dug in with Will very similar to what I do here,” Will told me. “I to learn exactly how much information the wanted to use math and quantitative tools to team’s data scientists have at their fingertips. help people solve real-world problems.” “Now, even versus three years ago,” said Will, He stuck to the plan while completing a post- “we get so much information. It’s tremendous, doc program in MIT’s Mechanical Engineering really.” He pointed from our window out across department, where he studied and predicted the field at the TrackMan radar unit that’s ocean waves. And while Will enjoyed academia, mounted over home plate—at Tropicana field he struggled with the degrees of separation and in every other Major League between his research and the boots-on-the- stadium in the country. The TrackMan—you ground team using his findings. guessed it—tracks the baseball at all times— when it’s thrown from the mound to the plate, That slight sense of disconnect was enough when it comes off the bat, you get the idea. to make him consider a career path outside Couple that with the stringers who are at every the traditional academic research track. A game, entering the information about who’s longtime baseball fan, Will took the plunge pitching, who’s at bat or on base, and you’ve and reached out to a handful of Major League got an insane amount of data. And thanks to Baseball teams about data science positions. the MLB’s standardized system—the TrackMan He loved the game, he was skilled at solving units and the stringers who work with the problems with data, and teams around the centralized group who manages them—Will country were starting to adopt a more data- and his team get this information the morning driven approach to recruitment and planning. after a game. It’s practically instantaneous.

Before long, Will was on the road to Tampa. So what does a real-world use case look like? And the rest, as they say, is history—and he Say the team is preparing for a series with a certainly doesn’t have to worry about being far team they faced earlier in the season. Thanks from the action these days. to TrackMan data, Will and his team can tell that their opponent’s for Game One has introduced a new pitch since their last Major League Data = Major League meeting. Because of that information, they can Data Science report out to the coaching staff so nobody is surprised at the plate. At this point, I’ll admit I was picturing Will as Jonah Hill’s character in Moneyball. Come It’s easy to see how having batting averages on—you can admit that you were too. And if or ERA numbers is useful at a glance. But you aren’t in the Will Cousins fan club already, the real magic happens when, like Will said,

3 With a skilled Research and Development team in the building, the Rays have made the paper-pushing, time-intensive processes a thing of the past. Now, the team can keep track of stats, outcomes, and patterns in a way that prepares them to make informed decisions for each and every game.

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you start to use those patterns to inform and patterns in a way that prepares them important team decisions. Say, for example, to make informed decisions for each and your shortstop gets injured and there’s every game. nobody on the bench who’s ready to take his place. You have some options, right? You could call up a player from one of your minor A Human Touch league affiliates, or you could make a for a new player. Even with a limited knowledge of the nuts and bolts of the work Will does—understanding Imagine making a call like this without a how to prioritize and segment data points to recommendation from a data scientist like perfect algorithms—it was easy for me to see Will or one of his colleagues. That’s how things that the human element is invaluable in this used to work—and it involved a lot more line of work. We see a lot of worry in today’s paper-pushing and manually sifting through world about machines and technology taking data comparisons. It sounds arduous, to say over our jobs, our decisions, our brains. But the least. Because of this, the process was that’s not what’s going on here. I saw Will’s time-intensive and often relied heavily on team with my own eyes—a fairly large group, luck and gut feelings. Because even if you actually—the brains behind the technology. know some of the statistics, it’s impossible to And for the people who think the team would understand their impact to your team without be larger were it not for the algorithms used to additional reporting. recruit players and make trades or prepare for that new pitch? I’d have to disagree. Without I asked Will about the scenarios when a the data science, I’d be willing to bet there decision needs to be made quickly. What wouldn’t be anyone else in the room. The ones happens when there’s an injury? Is it a wild- who were there just wouldn’t be as productive. and-crazy, all-hands-on-deck scenario? “It’s usually not that dramatic,” he told me In Tampa Bay, where leadership understands with a steady, friendly smile. “That would be the value a team of data scientists brings to really tiring, and the work would suffer. We table, there are plenty of perks aside from try to be prepared as much as we can. Sure, that view of the field. (Sorry, I’ll stop talking you can’t forecast when a player will get hurt. about it now.) For starters, there’s something But we can have some ideas about how we to be said for working with a group of like- use information and how we combine all the minded colleagues. The team, which is made data points we have. So then, when we’re in a up of scientists and mathematicians with position where there’s a time-sensitive need? backgrounds in everything from Statistics to You’ve done the tracking in advance so you Earth Science, is above average in size with don’t have to scramble as much.” regard to other Major League clubs. “Most of us were baseball fans before—and now?” said Will, Did you catch all that? With a skilled Research “We get to be right here, where the action is.” and Development team in the building, the Rays have made the paper-pushing, time- A perfect example of this is the club’s intensive processes a thing of the past. Now, willingness to think outside the box when the team can keep track of stats, outcomes, it comes to where and how the R&D team

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works. Earlier this year, Will and some of his Data Science is the Future teammates were invited to join the players and coaches in the for some of the Rays’ I couldn’t have come up with a better exhibition games. analogy myself. This is the beauty of today’s technology, right? We have access to the And at the end of the day, that’s what it’s all winning combination of highly skilled, well- about. Will brought up a perspective I could trained professionals who know exactly how relate to as we chatted about the future of to interpret data and decide how best to use data science and how the world reacts to it. it—for decision-making, for problem-solving, “One thing not everyone realizes,” he said, for process improvement. “is that there is very much a human role in data science and algorithm theory. There’s a This is necessary because, whether you’re Will misconception in a lot of people’s minds that receiving TrackMan stats the morning after data science or predictive modeling is just a Rays game or you’re Chief Legal Counsel that you pour this data into the computer, the for a multi-million dollar company combing computer will think, and spits out the answer.” through hundreds of pages of legal documents every day, there is so much data available in And I understand that misconception. As we today’s world. “And all that data tells us about built IntelAgree, CoLabs’ inaugural product, something we care about,” said Will. “Whether we sometimes got pushback from executives that’s what’s happening on a baseball field or when they learned about its functionality. “Are something in a document you’re looking for— you saying I should fire my entire legal team?” this data can help you answer your questions. they’d ask. (Of course not!) And usually the relationship between the data and the answer you’re looking for is Will spoke passionately about fallacies like complicated. So that’s why we need to use this. “That’s not what happens,” he said. “A these tools. Sifting through these volumes of human gets the data and thinks very carefully information is not easy to do.” about it. They decide the best way to use it to solve the problem at hand.” Take it from the Tampa Bay Rays—data science is here to stay, and it’s a game-changer. (No Then he glanced out across the outfield again. pun intended.) Get ready. “The computer is a tool for us,” he told me. “When a Major League player hits a , we don’t say ‘the bat crushed that one.’ The bat was their tool, and the player the In her role as Director of Marketing, Nikki oversees all the content that home run.” tells the story of CoLabs’ products. A writer and communicator at heart, Nikki comes from a diverse background of creative and strategic roles ranging from development of training curriculums for Fortune 500 companies, client account management, and nonprofit event planning. These days, when she’s not telling the world about CoLabs, you can find her spending time with her husband and two daughters in the suburbs of Richmond, Virginia.

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