The NBA Data Scientist

The NBA Data Scientist

#NBA #Data #Scientist

If you’re a basketball fan, you know your team’s big stars, head coach, maybe even the rookie bench warmers. But you probably know very little about the Ph.D. mathematicians like this woman. Her job is to crunch the numbers of the game. We’re all in sort of an arm’s race to acquire information.

And she’s turning basketball into a hard, cold science. My name is Ivana Seric and I’m a data scientist. For many years, Philly was a tough place to be a basketball fan. But having reached the top eight in the playoffs for a second season in a row,

The 76ers right now are in a renaissance. Embiid fakes, Embiid down the lane. Just across the river is where the team’s been hard at work and it’s where I went to go meet Ivana in April. This 125,000 square foot facility comes with all the features you’d expect from an NBA training complex.

It also features the office of people like Ivana who support the team behind the scenes. My job involves analyzing the data that we have from NBA games. My focus is mostly on the coaching strategy. Coaches have a lot of intuition. They know the game, they know the players,

But we try to complete their picture of the players with data, which is hopefully unbiased. Ivana is part of the Sixers 10-person analytics team. The work of these statisticians has already forced a profound change in the game of basketball. Teams are taking more three point shots. Embiid for three.

Even though we make them at lower percentage than the shots closer to the basket, but they’re worth more points and the trade off actually pays off. Take a look at this clip from the ’80’s. See how all the players are bunched up right by the hoop? Compare that with today.

More and more of the action is taking place at the three point line. Of course, it’s not just basketball that’s been reshaped by analytics. Businesses of all kinds are tracking a ton of information they never tracked before thanks to new sensors, improvements in computing power, implementing cost and data storage.

Data scientists are the people making sense of that information with a combination of statistics and computer programming. The profession’s expanded rapidly in recent years and comes with an average salary of $130,000 a year. Much of the data Ivana works with comes from technology the NBA adopted in 2013.

Every NBA arena has cameras that record the games and then from those cameras, they can extract player locations on a court. These cameras record 25 frames per second, so for each basketball game, there’s a million of throes of data. And that allows Ivana to analyze plays that were previously difficult to track.

For example, take the pick and roll. It’s one of the most important plays in basketball. It involves one player setting up a human shield to help a teammate shake off an opponent. So we can look at each player, how much they run pick and rolls and how good they are at that

And then we can select a player and see how often he’s going to pass out of the pick and roll, how often he’s going to shoot. And how would that help you develop a strategy for the coaches? So we could, for example this player, he’s going to pass pretty frequently.

We can say this to the coaches and they’re going to decide on the defensive strategy for the player. But this makes Ivana’s job look simpler than it actually is because she spends a lot of her time coding to extract the information she needs.

And I tried really hard to get her to talk about what exactly she looks for. And there’s some stuff that you do that’s beyond just these interfaces that you showed me today, right? Yep. Can you tell me more about that? Um, not really. So that’s like a trade secret? Yes.

NBA’s a very competitive league, so whatever can give us that advantage, we try to keep it. When advising the coaches with her analysis, Ivana has a decided advantage over many of her peers. I started playing when I was seven years old and I just loved it from the first day.

I think ’cause the game is so dynamic and there’s so many different skills. It’s what I wanted to do since I was seven years old, really. I wanted to be a professional basketball player. Yeah. At 19, Ivana moved from her home in Croatia

To New Jersey to go to college on a basketball scholarship. And while she was a star player on her Division I team, she was also an exceptional math student. Much of her life has been like that, balancing her love of basketball with her love of math.

I always thought I’m going to have to choose between the two. I went to graduate school and that’s when I really thought that, okay, I’m really choosing one or the other this time. So I thought I really chose just math. The plan was to become a researcher or a professor.

Then, three years into pursuing her Ph.D. in math, she heard that NBA teams were starting to hire data scientists, but only 26% of data scientists are women and Ivana didn’t like her odds. When I saw the job posting, I didn’t think I would actually get the job. I thought because being a woman

In such a male dominated field, they would never really consider me or give me a fair shot. But this prediction turned out to be wrong. She’s got both the technical and basketball backgrounds, which is sort of the ideal mix. Her ability to capture these complex insights

And then share them with players or coaches, with executives in a way that makes sense to us is super valuable and frankly, not that common. The next evening, I attended my very first NBA game. It was the last game of the regular season before the playoffs and my chance to catch up

With the ultimate beneficiary of Ivana’s work, the Sixers head coach, Brett Brown. The team has had a great season so far. What role do you think analytics has played in that success? I think it’s played a significant role in our success and many, many others.

The NBA playoffs are going to start in three or four days and immediately, we’ll get an analytical assessment on the strengths or weaknesses of an opponent. You can assess play calls, good or bad ones, ones you should do more, ones you should avoid. Really, I think it’s going to continue to grow

And play a significant role in the design of organizations and coaching staff’s beliefs. That night, even though none of the starting players played in the game, the Sixers ended up crushing the Bulls. A month later, the Sixers ended up advancing to the conference semi-finals and suffered a

Tough defeat at the hands of the Toronto Raptors. Is this the tie breaker? Ivana and her colleagues will keep looking for ways to help their team do better in the seasons ahead. But the Sixers victories on the court won’t be the only way she’s measuring her success.

It’s really exciting to be able to show young girls that they can actually have careers, but it also feels like a big responsibility because if I don’t do well, it’s going to seem like a woman cannot do this job, because there are not so many of us.

It’s a big part of what motivates me every day to be able to show young girls that they can succeed in STEM fields and in sports.

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