Final Five

Q&A with Rebecca Lally at ESPN

RebeccaLally650x488

In the summer of 2014, Rebecca Lally watched more games than even the most ardent sports fanatic. As a stats and analysis intern at ESPN, the IE senior from Georgia Tech fulfilled her dream of breaking down the numbers behind America’s most popular sports and teams for national TV.

Is your fascination with sports primarily about the games or the statistics behind them?

From early on in my childhood, I had an obsession with numbers and patterns. But I fell in love with sports in third grade when I began playing basketball and my father and brother began teaching me other sports. My true love became baseball, and I always looked for patterns. “Dad, look! It’s two balls, two strikes, two outs and there’s a man on second base.” I recorded games in game books as I watched on television and attended a number of games at Turner Field, with the occasional summer trip to Fenway Park.

When did you first realize that industrial engineering could be applied to sports analysis?

After my freshman year of college I figured out that industrial engineering would be the perfect fit for me. I had known since sixth grade that I wanted to go into sports statistics. I began at Georgia Tech as an applied mathematics major until ... I found industrial engineering and attended an information session. I immediately switched and was reassured through my class topics that this could easily be applied to sports analytics.

What was your primary role at ESPN?

I was a stats and analysis intern, and I focused on real-time data tracking for Major League Baseball as well as creating statistical-based stories for fans to consume. ESPN has unique data tracking tools for each sport, and my daily responsibilities for baseball included updating the runs, hits and errors of a game as they happened to populate the data on ESPN.com, the BottomLine ticker on ESPN TV channels and mobile alerts for the SportsCenter app. I was also in charge of monitoring the game for any potential top plays, home runs, injuries and ejections.

Did you feel any added pressure analyzing data in a breaking news environment?

One of the purposes of real-time data tracking for each sport is so that ESPN can be timely with score updates. It’s important not to report scores inaccurately because of the vast number of fans that consume ESPN content every minute. The amount of pressure I felt while at ESPN was a healthy amount; it didn’t make for a stressful environment but instead kept everyone focused and motivated.

Are there some sports that are more difficult to analyze in real time than others?

Basketball and baseball are the most advanced in terms of metrics used to analyze games, with football following closely behind. Although metrics are being created and modified rapidly for all sports, I believe hockey and soccer are games that are more difficult to analyze because of the limitations on game components to be measured and analyzed and due to the rapid speed of play. Also, the current consumption in America is primarily football, baseball and basketball, thus [they are] the main areas of focus for analytics not only for consumers, but for teams to recruit and offer contracts.

– Interview by David Brandt

David Brandt is the Web managing editor for IIE.

*This article has been corrected from a previous version.

SHARE