Sports analytics field grows, attracts student interest

October 28, 2019 — by Preston Fu and Christine Zhang

Data analysis grows to be as prominent as the gameplay itself

Junior Proby Shandilya was proud to showcase his summer research on investigating the value of NBA players based on their impacts to their teams at the University of Connecticut Sports Analytics Symposium on Oct. 5. College professors and more than 100 high school and college students from across the nation arrived to check out each other’s work.

“I met a lot of really cool people in the industry,” Shandilya said. “It took me a long time to come up with the project, but it was a really great experience working with hands-on sports team data.” 

Sports analytics is the practice of applying mathematical and statistical principles to sports. According to Forbes, it emerged as a field in 2003 when financial journalist and author Michael Lewis published his book “Moneyball,” a work that documented the first known use of statistics and data to make decisions on professional sports. Recent advances in data collection and management technology have made the field more popular, and now, a large portion of professional sports teams use sports analysts to improve their rosters.

Shandilya has not only done individual research on sports analytics but has also brought its increasing popularity to the school. In his sophomore year, Shandilya founded the Sports Analytics club on campus, which meets every other Thursday in special education teacher Danny Wallace’s room. 

Shandilya likes sports analytics because it connects two topics that both interest him.

“Sports analytics really seemed like a fun way to combine skills in technology and engineering to my passion with sports,” Shandilya said. 

  Shandilya has always loved sports. He started a sports statistics blog eight years ago as a mere third grader. His interest in analyzing sports has since flourished; in his freshman year, he wrote a self-published book titled “Surrounding Factors: Explore What Determines The Success Of NBA Greats.” In it, he analyzed how an NBA player’s performance is determined by how his teammates complement his playing style.
Shandilya eventually narrowed his interest to sports analytics. He is taking AP Statistics to add to his ability to analyze quantitative data. 

“I think it's more important to learn the statistical and advanced computational techniques [before going into sports analytics],” Shandilya said. “The passion for sports will always be there, so you can always apply your skills to sports data.”

As for his Sports Analytics club this year, Shandilya is planning to focus on teaching data science techniques. He said he will try to work with some of the school’s sports teams and hopefully increase student interest in sports analytics. 

Shandilya said sports analytics do not make much of an impact for the players themselves but rather do so more for the coaches. 

“I think it helps way more in strategy than actually playing,” he said. “From a manager’s perspective, when you're seeing which players you want for your team, looking at the analytics and seeing which players really make an impact on winning can help strategize.”

The use of analytics for sports managers was first introduced through baseball. Oakland Athletics’ General Manager (GM) Billy Beane created a team consisting of players with high on-base percentages, and the A’s immediately began earning more walks than strikeouts.

Oakland isn’t alone in their increasing usage of analytics: the number of baseball Ivy-leaguer GMs has been on the rise. While previous professional teams had gathered in hotel gyms the morning of the game, modern GMs meet with their large staff late at night, scanning over raw spreadsheet data and old videos. The gameplay itself is now beginning to coalesce with its once-independent analysis.

Recently, sports analytics has also come to impact other sports such as basketball. According to Forbes, NBA teams now use a form of technology called “Player Tracking” to evaluate the efficiency of a team by analyzing player movement. 

Senior Bryan Chu has been interested in statistics since his freshman year. In the summer after his sophomore year, he took a six-week statistics course at Stanford University, and this past summer, he went to the University of Pennsylvania to participate in the Wharton Moneyball Academy, a program that focuses on statistics in sports. 

Chu said the program taught basic topics in statistics using data from sports, which introduced him to sports analytics. Through the program, he also met guests who worked in the NBA and NFL. 

“They talked to us about how statistics is changing the game, especially as sports analytics are becoming more and more prominent,” Chu said. “Ten years ago, there would only be a couple people on the analytics department of a sports team, but now, there are 10 or 20 in each department.”

He feels that sports themselves have always been popular, but the rise in interest in sports analytics has grown due to today’s emphasis on technology.

The rise in sports analytics has spread not only to professional sports but also at the high school level. Wallace, who also coaches the varsity girls’ basketball team, said that he has used the sports analysis program Hudl for the past three years to determine which players are best suited for which positions and which players work best together. This way, he can create plays to move the ball in such a way that maximizes the number of points the team can score.

“If we look at the game film, we can only see so much,” Wallace said, “but the stats don’t lie. They allow us to see so much more, and it really does help a lot.”

At the same time, Wallace does recognize the shortcomings of programs like Hudl: Coaching can’t be entirely based on analytics. There are still other important aspects to consider like team bonding and health. 

“It may have worked well for the Oakland A’s, but baseball is essentially an individual sport,” Wallace said. “There’s only one person up to bat at a time. The same thing won’t work so well for basketball.”

For his part, Chu plans on going into statistics or another mathematical field, while Shandilya said he is interested in sports technology and sports analytics as a career. 

“I think we're in a golden age where we can really use technology to change, innovate and revolutionize sports,” Shandilya said.