Berkeley Sports Analytics and San Francisco Giants Case Competition

This was a speech I gave in 2017 to open the Berkeley Sports Analytics and San Francisco Giants Data Science Case Competition.

Hello Everyone, my name is Derek Topper and I’m the President and Founder of the Sports Analytics Group at Berkeley and I’d like to welcome you to the 2017 Berkeley Sports Analytics and San Francisco Giants Data Science Case Competition.

Before we start I’d like to thank the great people and organizations that made this event possible. Specifically I’d like to thank Michael Gries of the San Francisco Giants, Stacey Dorton and Anthony Suen from Berkeley Institute for Data Science, the SAGB Board, Max Weinstein, Ari Pickar and Rohan Narayan as well as Harrison Shane, Kevin Quigley, Brenden Hurston, Ashish Reddy, Jon Rutchik, Sid Girkar and the entire Business committee, for their tremendous efforts in putting this event on. I’d also like to thank all of you guys for partaking in this great event as well as every one of the club leaders who helped promote this event to their members.

As we get the ball rolling, I’d like to tell you a little bit about who Sports Analytics Group at Berkeley is, what we do and what we’re planning in the future.

Sports Analytics Group at Berkeley is a student group that aims to educate members about the fields of Sports Analytics, Data Science and Sports Business through research, data journalism, event management and consulting via an application-based approach to learning.

At the Sports Analytics Group at Berkeley, we consider ourselves to be “trailblazers.” This moniker stems from the fact that we are the only club on campus to focus exclusively on bridging the gap between Sports and its business and analytics counterparts. While other groups on campus focus on Data Science or Sports Business, we are the only group that directly focuses on juxtaposition between the two. In this way, we use our resources to focus on what is needed to make it in the modern Sports climate. Everybody wants to work in sports, but our club prepares members for such a job by providing technical skills and combining them with sports business. Weve been pretty successful so far, organizing events like this and getting our members internships with the Oakland Athletics, Milwaukee Brewers, Brooklyn Nets, the New York Mets and Adidas, to name a few, as a result of the experience they’ve gained from SAGB.

This is a topic that’s been of particular interest to me for a very long time. One of my earliest memories is my father showing me how to read the baseball box scores the day after my first visit to Yankee Stadium. I was fascinated how the game I had just witnessed could be magically encapsulated in simple numeric tables. Yet there was more. On the page before me was every play from every game, team rankings, player stats, and league leaders. My mind reeled.

From that moment, I loved the Yankees and their short-stop as only a kid named Derek could. It became my morning ritual to open the back of the newspaper and pour over the stats analyzing how Jeter did that day and what was going on around the league. At night, I dreamed of playing for the Yankees.

By the age of 14, I realized that my dream of heading to the Bronx was not likely to become a reality but about the same time I was accepted into my first academic summer program. I spent the next four summers studying different forms of statistics and mathematics through Johns Hopkins University and Williams College. I was tried to learn as much as I could about sabermetrics as well as how to run a baseball team. I realized that if I couldn’t be Derek Jeter, then I’d rather be like George Steinbrenner or Brian Cashman. The things I learned built upon my innate fascination with statistics and expanded my interest in applying math beyond baseball.

It was this desire that led me to found this club here at Berkeley. Since last spring, when our organization was first chartered, the Sports Analytics Group at Berkeley has rapidly grown into one of the premier Data Science clubs on campus. This is something that I never could’ve predicted, considering I had never even heard of the field of Data Science nor seen a Python script before I came to Cal. In fact, neither my high school nor any of the neighboring ones offered a single computer science course. The closest thing to programming that I had done was teach myself to use HTML so I could create Wikipedia pages for international sporting tournaments. In that way, coming to Berkeley, and taking various computing courses, essentially led us here today.

I met Max at a party, and we talked about how we were both passionate about this particular branch of data science. Max had just finished an internship with the Brewers and I’d finished working for two little known sports companies. After his initial conversation, we met up again to develop what would become the the framework for SAGB and brought on Rohan and Ari to help us in strategic areas that we desperately needed.

Eventually, we held our first infosession last November and attracted two hundred applications to join. After a rocky first semester, we have quickly grown in top campus organization. Now, we have 75 people separated into three teams.

This is where we are today, with segments of our club exploring research, data journalism and sports business.

Our research team explores new issues in Sports analytics, and works on topics ranging from the effects of NBA rule changes to how physics affects an MLB pitch. Focusing on longform papers, the research team prepares projects that are conference-ready and has weekly meetings to work on their projects and share their ideas. This team of about 40 people follows a very unstructured timeline giving members free-reign to work on projects at their own pace. Run by Max, a GSI for Probability 140, the team is hoping to submit their work to the MIT Sloan Conference next semester.

Our data-journalism team has monthly deadlines with the 20 members writing one data journalism article every month. Each member writes a short-form data-centric article about a topic in sports and works on them throughout the month. The team regularly receives workshops on data science topics like visualizing data and data wrangling, so they can create articles through application-based learning. This semester we’ve had articles on MLB spending efficiency and average goals per period in overtime and regulation in hockey.

The team, run by myself, should have over 40 articles on our website by the end of the semester.

Lastly, our business team puts on events like this one! In addition to organizing our case competition, the business team puts on our Sports Professional Development Workshops, manages social media, organizes various internal and Social events, and arranges consulting opportunities. The team also plans our SAGB Speaker Series, which has had speakers ranging from Berkeley professors to MLB front office staff to the winner of the NFL Hackathon, and has had a tremendous impact on bringing sports operations, analytics, and decision-making to the Berkeley campus.

Consequently, I believe that today’s event is the first step in a great future for this club. In the coming semesters, we expect to have both a projects team and a dedicated consulting team, to help local teams and allow our members to gain valuable experience in the field. We expect to partner with other campus groups to continue to bring top sports minds to our campus. We expect to continue to build our alumni base and to help connect our members with analysts from their favorite pro teams. With a little luck, we also eventually hope to put on a Berkeley version of the MIT Sloan sports analytics conference. While this may be a pipe dream, it’s always good to set high expectations. Yet our ultimate goal is to continue to partner with major sports organizations to provide Berkeley and its students with the opportunity to get a real taste of preparing the same type of analysis that a team may make on a daily basis.

While SAGB maybe a relatively new club, we have lofty ambitions for ourselves. Whether or not we meet them, we plan on providing the juxtaposition between sports and data science for years to come.

Finally, in terms of today, I’d like to wish all the teams good luck and hope you all come away having learned a little bit about this field I hold dear.

Thank you for your time and I’ll now pass the podium over to our other president Maxwell Weinstein.

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