Moneyball Academy

Sponsored by the Wharton Sports Analytics and Business Initiative (WSABI), the Wharton Moneyball Academy is a three-week summer program that provides an opportunity for rising high school juniors and seniors to study sports analytics at the Wharton School of the University of Pennsylvania. This program focuses on using data to make deep discoveries in sports with a focus on becoming a data-driven decision-maker. Instruction will focus on fundamentals of statistical thinking, real applications employed by statistics professionals in sports analytics, and an introduction to statistical programming languages.

Overview

Sponsored by the Wharton Sports Analytics and Business Initiative (WSABI), the Moneyball Academy primes students to become leaders in an increasingly data-driven economy.

Taught by Professor Adi Wyner, the Moneyball Academy teaches students how to apply advanced statistical concepts to sports analytics—beyond what’s typically covered in AP Statistics. The curriculum draws from several Wharton courses (STAT 101, 470, and more) and includes hands-on coding in R, the programming language used by professional statisticians. Students will learn to conduct the types of analyses featured in outlets like FiveThirtyEight and Fangraphs.

Students collaborate on a final data analytics project, with the chance to be published in the Wharton Sports Analytics Journal. The program also features guest speakers from the world of professional sports, such as executives and data scientists from the Washington Nationals, Los Angeles Lakers, and Philadelphia Eagles.

This program is ideal for students with a strong background in math and a love of sports. An interest in computer programming is strongly recommended but no specific background is necessary.

Each summer, Wharton Moneyball Academy students:

  • Gain a rigorous introduction to sports analytics, learning how data drives decisions in professional sports.
  • Build a strong foundation in statistics and probability, including data visualization, regression, and hypothesis testing.
  • Learn to use R programming for real-world data analysis and to create your own visualizations.
  • Apply data science methods to real sports datasets, mirroring the work of professional analysts at places like FiveThirtyEight and FanGraphs.
  • Develop critical thinking and quantitative reasoning skills through lectures, coding labs, and team projects.
  • Engage with guest speakers from the sports analytics industry who share insights into careers and applications of data in sports.
  • Collaborate in teams to complete a capstone research project in sports analytics, presented on the final day of the program.

All participants who complete the program will earn a Wharton Global Youth Certificate of Completion.

Details

Academic classes are held Monday-Friday with extracurricular activities available in the evenings and on the weekends. Students move in on Sunday pre-program, and move out the final Saturday of the program. For more information on campus life, visit our residential experience page.

While each day varies slightly in format, a typical day includes:

  • 9:00-10:30am – Morning lecture
  • 10:30-10:45am – Mid-morning break
  • 10:45-12:00pm – Office hours
  • 12:00-1:30pm – Lunch
  • 1:30-3:00pm – Guest speaker
  • 3:00-3:15pm – Afternoon break
  • 3:15-4:30pm – Computing in R lecture
  • 4:30-5:30pm – Breakout sessions and group work

Session topics may include:

  • Introductory statistics (including graphical and numerical summaries of data)
  • Basic probability theory
  • Statistical reasoning
  • Regression analysis by examining sports data

In the evening, students will have a number of extracurricular activities to choose from. Students can also opt to work on their final project with their group, meet with the program TAs, and/or relax at the dorm.

Please note, some days may not follow this schedule as there could be a site visit off campus or a simulation in lieu of lecture/recitation schedule.

Eligibility

Eligibility

High school students currently enrolled in grades 10-11 with a strong math background and a love of sports. An interest in computer programming in strongly recommended, but no specific experience or background is required. International applicants are welcome.

Admission

Admission to the Moneyball Academy is selective. Wharton will select approximately 75 students to attend the Academy. Selections are based on a record of academic excellence, demonstrated math skills, and a genuine interest in sports analytics. Interested students are encouraged to submit an application by the priority deadline.

Please note that participation in the Moneyball Academy program does not guarantee admission into Penn.

Instructional Team

Faculty Leader: Adi Wyner
Professor Wyner received his Bachelors degrees in Mathematics from Yale University, where he graduated Magna Cum Laude with distinction in his major. He was the recipient of the Stanley Prize for excellence in Mathematics. His PhD in Statistics is from Stanford University, where he won a National Science Foundation Graduate Fellowship, the Abrams Prize and the Herz Foundation fellowship. After graduating from Stanford, he received the NSF post-graduate fellowship and a visiting Professorship at the University of California, Berkeley. Dr. Wyner has been a Professor of Statistics at the Wharton School of Business for the last 11 years. He is a tenured Professor and the Chair of the Undergraduate Program in Statistics and Data Science for the University of Pennsylvania.

Teaching Assistants
Teaching Assistants consist of both undergraduate and graduate students from the University of Pennsylvania. TAs facilitate small-group discussions, ensure student understanding, assist with final project development, and hold office hours to answer student questions and share their Penn and Wharton experiences.

“My favorite part of Moneyball Academy was undoubtedly having an opportunity to listen to AMAZING guest speakers' stories and advice on sports management and data analysis." - Byeongzu K., Istanbul, Turkey