CMSACamp Project Showcase
Join us in highlighting and celebrating Summer 2021 Carnegie Mellon Statistics & Data Science Undergraduate Research Experience, aka Carnegie Mellon Sports Analytics Camp!
The Department of Statistics & Data Science offers a 8-10 week Summer Undergraduate Experience with the theme Data Science in Sports Analytics. While the applications are in sports analytics, the program is focused on developing skills in statistical and data science methodology and being able to apply these skills to a wide range of problems and contexts. Professional skills development is also emphasized.
The program culminates in a final group project with external clients/advisors. Below you'll see this year's projects via short 10-min overview videos, slides/websites, and moderated zoom rooms where participants will be available to to answer questions about their work.
Zoom links will be made available on this site from 3-4pm EDT. Sessions will be moderated; any participants using inappropriate language or creating an unprofessional or unsafe environment will be removed and blocked at the discretion of the moderator.
Final Projects
| Maximizing wOBA with Launch Angle and Exit Velocity (with Adam Brodie, Houston Astros) Brooke Coneeny (Swarthmore College), Erin Franke (Macalester College), Sarah Sult (Washington University in St. Louis) |
Slides | Presentation | Zoom |
| Modeling Player Fatigue in the NBA (with Max Horowitz, Atlanta Hawks) Grace Fain (University of Oklahoma), Austin Stephen (University of Wyoming), Matthew Yep (University of California, Berkeley) |
Slides | Presentation | Zoom |
| Modeling Soccer Dynamics and Predicting Scores with Potential Functions (with Kostas Pelechrinis) Nicholas Ho (Arizona State University), Sifan Tao (University of Virginia), Adhvaith Vijay (University of California, Los Angeles) |
Slides | Presentation | Zoom |
| A Deep Dive into Expected Goals (with Sam Ventura, Brian Macdonald) Sara Armstrong (Elon University), Devin Basley (Earlham College) |
Slides | Presentation | Zoom |
| Run vs. Pass Play Prediction: Incorporating NFL Tracking Data (with Sam Ventura, Brian Macdonald) Tej Seth (University of Michigan), Nicole Tucker (University of Evansville) |
Slides | Presentation | Zoom |
| Predicting Shot Outcomes in the NHL (with Sam Ventura, Brian Macdonald) Claire Dudley (St. Lawrence University), Ruby Wu (Emory University) |
Slides | Presentation | Zoom |