From the Editor • Spring 2026
Katherine Comer, W’26
Former Editor-in-Chief
Dear Readers,
I’m excited to share with you the Spring 2026 edition of the Wharton Sports Analytics Journal. This edition features creative research questions and methods covering international soccer, fencing, hockey, and other popular sports.
As my last year as Editor-in-Chief comes to a close, I’m immensely proud of how the journal has grown to become a coveted destination and resource for young researchers to share and learn more about the growing field of sports analytics. It’s been an honor to head this publication, and I’m excited to pass the reins to Mukul Anand to continue to uphold the journal’s mission as the next Editor-in-Chief. We stand committed to being a platform where students can showcase research and foster knowledge among others in the sports analytics community.
As always, I’d like to invite any high school, undergraduate, or graduate student doing research in sports analytics or sports business to submit their work to the journal. We would love to consider your submission for our upcoming editions.
We hope this edition helps spark new curiosities about what questions can be asked about the world of sports and what methods can help you find answers. As always, please let us know your thoughts and feedback as we strive to bring you the best of sports analytics.
Sincerely,
Katherine Comer, W’26
Editor-in-Chief
Spring 2026
A Unified Server Quality Metric for Tennis
A Unified Server Quality Metric for Tennis, authored by Aiwen Li, University of Pennsylvania, Amrita Balajee, University of Pennsylvania, Harry Wieand, Boston University Academy, Jonathan Pipping-Gamon, University of Pennsylvania. Read More
Beyond the Expert: An Algorithmic Approach to Correcting Expert Bias in Fantasy Football Projections
Beyond the Expert: An Algorithmic Approach to Correcting Expert Bias in Fantasy Football Projections, authored by Vishnu Datta Jayanti, Allen High School, Allen, Texas. Read More
Performance Analysis in the Brazilian Soccer League: Applying Machine Learning Techniques to Team Evaluation
Performance Analysis in the Brazilian Soccer League: Applying Machine Learning Techniques to Team Evaluation, authored by José Vinicius Boaventura Barbeiro, Universidade Tecnológica Federal do Paraná (UTFPR), Londrina, Brazil Read More
Kicking for Goal or Touch? An Expected Points Framework for Penalty Decisions in Rugby Union
Kicking for Goal or Touch? An Expected PointsFramework for Penalty Decisions in Rugby Union, authored by Kenny Watts, University of Pennsylvania and Jonathan Pipping-Gamón, University of Pennsylvania. Read More
Integrating Dynamic Defensive Geometry and Match-State Context in Probabilistic Shot Quality Assessment: An Advanced Expected Goals Modeling Framework
Integrating Dynamic Defensive Geometry and Match-State Context in Probabilistic Shot Quality Assessment: An Advanced Expected Goals Modeling Framework, authored by Shriyansh Singh, Middleton International School Tampines. Read More
Opponent-Adjusted Evaluation of NFL Pass Blocking and Pass Rushing Performance
Opponent-Adjusted Evaluation of NFL Pass Blocking and Pass Rushing Performance, authored by Jonathan Pipping-Gamón, University of Pennsylvania, Maximilian Gebauer, University of Pennsylvania, Victoria Lee, University of Pennsylvania, Kenny Watts, University of Pennsylvania, Abraham J. Wyner, University of Pennsylvania. Read More
The Contract Effect: Why NHL Players Perform Differently When Money Is on the Line
The Contract Effect: Why NHL Players Perform Differently When Money Is on the Line, authored by Vanessa Palisin, Presbyterian College. Read More
Real-Time Basketball Jumpshot Detection on iOS: A Comparative Analysis of Linear Regression and Random Forest Classification Using Apple’s Vision Framework
Real-Time Basketball Jumpshot Detection on iOS: A Comparative Analysis of Linear Regression and Random Forest Classification Using Apple’s Vision Framework, authored by Davis Meng, The Groton School, Groton, Massachusetts. Read More
Age-Structured Transition Analysis of Competitive Exit in U.S. Fencing: Continuation, Temporary Absence, Return, and Terminal Non-Return
Age-Structured Transition Analysis of Competitive Exit in U.S. Fencing: Continuation, Temporary Absence, Return, and Terminal Non-Return, authored by Jeremiah Liu, Lexington High School, Lexington, Massachusetts. Read More
All-Star Based Evaluation of Draft Value Curves Across Major North American Sports Leagues
All-Star Based Evaluation of Draft Value Curves Across Major North American Sports Leagues, authored by Jordan Abell, Latin School of Chicago, Felix Soloway-Gilbert, Pilgrim School, Jonathan Pipping-Gamón, University of Pennsylvania, and Abraham J. Wyner, University of Pennsylvania Read More
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