Carnegie Mellon Sports Analytics

Welcome to the home page of Carnegie Mellon Sports Analytics. A strong believer in open source reproducible research and broadening outreach, access, and opportunities in sports analytics, CMSAC is a collection of initiatives at Carnegie Mellon with leadership in the Department of Statistics & Data Science and partnerships in the Pittsburgh area, amateur and professional sports, media, and related industries.

Click on each section to learn more about our projects and initiatives. If you would like to partner or get involved, feel free to email

Statistics in Sports Research Group

One of the primary goals of Carnegie Mellon Sports Analytics is to push forward the sports analytics discipline through the dissemination of cutting edge research that also contributes to both applications and statistical methodology. Below are some of our most recent papers:

Open Source Sports Podcast

Ron Yurko and Kostas Pelechrinis host the Open Source Sports podcast as a public reading group for discussing the latest resaerch in sports analytics. Each episode focuses on a single paper feturing authors as guests, with discussions about the statistical methdology, relevance, and future directions of the research.

You can find it on Apple Podcasts , Spotify, Google Podcasts, and Anchor .

  • First episode: openWAR with Gregory J. Matthews (Loyola)

Carnegie Mellon Sports Analytics Conference

The Department of Statistics & Data Science and the Carnegie Mellon Sports Analytics Club are proud to host an annual (mid-fall) conference focusing on high-quality, cutting edge sports analytics research with a strong emphasis on community and supporting the next generation.

We look forward to having you join us!

Carnegie Mellon Sports Analytics Camp

The Department of Statistics & Data Science offers a 8-10 week Summer Undergraduate Research Experience with the theme Data Science in Sports Analytics. While the application area is 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.

Students will learn from faculty and experts in the field, culminating in a group project with an external partner in sports analytics. There is a strong focus on diversity, equity, and inclusion and building pipelines into STEM fields and sports analytics. Students are financially supported through a $4000 stipend and housing. (The 2020 and 2021 programs are virtual.)

Learn more and apply at!

This year's Application Deadline: February 28, 2021.

Carnegie Mellon Sports Analytics Club

The CMU Sports Analytics Club is an undergraduate student-run sports statistics club which uses in-depth quantitative data to develop our members’ understanding of sports analytics, strategies, and management. The club actively seeks new members year round to research and write articles on a variety of sports, develop leadership skills, and participate in analytics competitions. If you’re interested in sports analytics, learning more about it – and potentially making a career out of it – contact Learn more here.

Tartan Sports Analytics

In 36-493: Sports Analytics, we partnered with the Carnegie Mellon Athletics Department on a set of ground-breaking projects that integrate previously unlinked, disparate data sets to build interactive applications and statistical models that can be used by coaches and staff to better understand and predict student-athlete performance.

Feel free to explore the current projects below.

Spring 2020 36-493 : Professor Rebecca Nugent

Golf Performance (with CMU Men's and Women's Golf)
Marc Edwards, Yedin Liu, Xinzhe Qi
Poster   App 5-min Presentation Feedback
Carnegie Mellon Softball Pitcher Efficiency (with CMU Softball)
Gautam Goel, Scott Steinberg
Poster   App 5-min Presentation Feedback
Swimming Top Time Trajectories (with CMU Women's Swimming)
Megan Christy, Julia Miraglia, Omkar Sakhawalkar, Shwetha Venkatesh
Poster 5-min Presentation Feedback
Using Text Analysis to Evaluate Softball Run Expectancy (with CMU Women's Softball)
Sean Jin, Zachary Siegel, Anna Tan
Poster   App 5-min Presentation Feedback
Basketball Logistics and Performance Indicator Analysis (with CMU Men's Basketball)
Violet Dong, Ryan Mahtab, Shurui Zeng
Poster 5-min Presentation Feedback