Justin Ehrlich

Education

• Ph.D., University of Kansas, Lawrence, KS
• M.S., Wichita State University, Wichita, KS, . Major: Computer Science
• B.B.A., Friends University, Wichita, KS, . Major: Accounting and Business Administration

Specialization

• Sport analytics and data science, Spatial analysis in sport (shot charts, player tracking), Golf performance analytics, Machine learning applications in sport, and Data visualization and interactive dashboards

Teaching

Teaching Interests

• Dr. Ehrlich teaches programming, data science, and analytics courses that prepare students to work with complex sports data. His courses include R for Sport Analytics, Python for Sport Analytics, Football Analytics Applications, Golf Analytics, and introductory programming courses for the Sport Analytics certificate and master's programs. His teaching emphasizes active learning through hands-on projects that mirror real-world analytics workflows, including data wrangling, visualization, web scraping, interactive dashboard development, and statistical modeling. His teaching philosophy centers on learning by doing. Rather than assigning many small exercises, he designs large, creative projects that require students to synthesize concepts and apply them to authentic problems. He believes diverse backgrounds strengthen the learning environment and builds flexibility into assignments so students can leverage their unique interests and experiences. His commitment to teaching excellence has been recognized with multiple awards, including the Provost's Award for Academic Excellence in Teaching with Technology.

Currently Teaching

• SAL 606 - Applications of Machine Learning for Sport Analytics using Python
• SAL 690 - Independent Study
• SAL 602 - Introduction to R for Sport Analytics
• SAL 605 - R for Sport Analytics II

Active Research

Research Interests

• Dr. Ehrlich's research program integrates computer science, statistics, and sports domain expertise across three interconnected areas: the business of sport, rating and ranking systems, and on-field performance analysis, with particular emphasis on spatial analytics and golf performance research. His recent golf research, conducted in collaboration with the University of Nevada, Las Vegas, investigates performance optimization through biomechanical and environmental analysis. This work examines how weather conditions affect player performance, optimal swing sequencing patterns, and the relationship between swing consistency and scoring outcomes. These studies apply advanced statistical modeling to high-resolution performance data, contributing to both theoretical understanding and practical applications in player development. In basketball, Dr. Ehrlich has developed novel approaches to spatial analysis through advanced shot charts. Traditional shot charts omit critical information that distorts decision-making; his "True Shot Charts" incorporate location-dependent points from free throws pursuant to made field goal attempts and account for missed shots that result in shooting fouls. This spatial approach provides a more accurate representation of shot value by location, enabling better strategic analysis for teams and analysts. This research was recognized as a finalist at the 2024 MIT Sloan Sports Analytics Conference Research Paper Competition. His business of sport research has identified market inefficiencies in player valuation, demonstrating that NBA and MLB teams systematically overpay offensive players relative to defensive counterparts despite equivalent on-court value, presenting opportunities for win-maximizing arbitrage. His rating and ranking work examines how scoring systems introduce noise into competitive outcomes, including computational analysis of social choice violations in NCAA competitions and improvements to expected win models through difference-form and serial contest success function alternatives to the Pythagorean expectation. Dr. Ehrlich's on-field performance research leverages natural experiments to isolate causal effects. Using COVID-era attendance restrictions, he demonstrated that home advantage in both the NBA and NFL is fully attributable to crowd presence. He also co-authored the winning paper at the 2025 MIT Sloan Sports Analytics Conference Research Paper Competition, which examined penalty kick strategies. Additionally, he contributes to public health through the Falk College CTE in Sport Research group, where he developed the professional football Cumulative Head Impact Index (pfCHII) and has published findings on mortality risk factors among NFL players in JAMA Network Open.

Sponsored Research

• Yaejin Moon (PD/PI) Justin Ehrlich (Co-Investigator) Senem Velipasalar Gursoy (Co-Investigator) , Understanding Biomechanics Of Real-Life Falls Using Pose Detection Algorithms - National Institutes of Health (NIH)/DHHS - Federal Agencies Grant. End Date: 2027-11-30
• Yaejin Moon (PD/PI) Justin Ehrlich (Co-Investigator) Senem Velipasalar Gursoy (Co-Investigator) , Understanding Biomechanics of Real-Life Falls Using Pose Detection Algorithms - National Institutes of Health (NIH)/DHHS - Federal Agencies Grant. End Date: 2027-03-31

Published Scholarship

Publications

• Simion, A., Ehrlich, J., Upton, J., Oettl, W. and Sanders, S., 2025. Equal Financial Benefits? Title IX Gender Discrimination Behavior in National Collegiate Athletic Association Programs. Journal of Sport Management, [online] pp.1–14. https://doi.org/10.1123/jsm.2024-0383.
• Potter, J., Ehrlich, J., Fossum, L., Sanders, S., Vignesh, A., Bhatt, S. and Sanders, S., 2025. F1 Versus Indy: Analyzing a Unique Shared-Course Natural Experiment to Determine the World’s Fastest Auto Racing Format. American Behavioral Scientist. [online] https://doi.org/10.1177/00027642251366044.
• Ehrlich, J., Kneiss, C., Geise, H. and Howland, C., 2025. Assessing Home-Field Advantage in the Presidents Cup: Impact on Competitive Balance and Team Performance. Available at: <https://zenodo.org/doi/10.5281/zenodo.17305063>
• Medcalfe, S. and Ehrlich, J., 2025. What’s in a Name (Image, and Likeness)? American Behavioral Scientist. [online] https://doi.org/10.1177/00027642251366021.
• Medcalfe, S., Hasija, D., Ehrlich, J. and Roumpi, D., 2025. Diversity and Team Performance: Evidence from the Indian Premier League. American Behavioral Scientist. [online] https://doi.org/10.1177/00027642251366054.
• Ehrlich, J., Sanders, S., Potter, J. and Fossum, L., 2025. F1 v. IndyCar in the Technological Competition for Race-Speed Supremacy: Continuous, GAM-Estimated Speed-Differential Estimates from a Shared-Course Natural Experiment. American Behavioral Scientist. [online] https://doi.org/10.1177/00027642251366038.
• Simion, A.M. et al., 2025. Equal Financial Benefits? Title IX Gender Discrimination Behavior in NCAA Athletics. Journal of Sport Management.
• Cain, C., Lee, J., Handley, E., Merrell, D., Ehrlich, J. and Paul, R., 2025. Golf Analytics. Digital Transformation in Sports, [online] pp.6–30. https://doi.org/10.1201/9781032665191-2.

Presentations

• Uribe, A. et al., 2025. Do Behavioral Considerations Cloud Soccer Penalty-Kick Location-Optimization? Game Theory, GAM, and Lasso Analysis. In Harvard University. New England Symposium on Statistics in Sports.
• C.K., Geise, H. & Ehrlich, J., 2025. Assessing Home-Field Advantage in the Presidents Cup: Impact on Competitive Balance and Team Performance. In Music City Center. Joint Statistical Meetings. American Statistical Association.
• Cain, C. et al., 2025. Leveraging Technology to Accelerate Growth and Innovation in Golf. In Bellagio Hotel and Casino. SEICon II.
• Ehrlich, J., 2025. Team Dynamics and Home Continent Advantage: Europe’s Dominance in the Ryder Cup. In MathSport International. University of Luxembourg.
• Bhatt, S. et al., 2025. Formula One versus IndyCar: A Unique Shared Course Natural Experiment at Circuit of the Americas. In Yale University. Connecticut Sports Analytics Symposium.
• Sanders, S.D., Uribe, A. & Ehrlich, J., 2025. Do Behavioral Considerations Cloud Penalty-Kick Location Optimization in Professional Soccer? Classical/Statistical Game Theory & Empirical Testing using Polynomial and ML Regularized Lasso Regression. In Yale University. Connecticut Sports Analytics Symposium.
• Geise, H., Kneiss, C. & Ehrlich, J., 2025. Partner Effects and Performance: Exploring Pairing Dynamics in Professional Golf. In The Ohio State University. 5th Annual Ohio State Sports Analytics Conference.
• Uribe, A. et al., 2024. Do Behavioral Considerations Cloud Penalty-Kick Location Optimization in Professional Soccer: Game Theory & Empirical Testing using Polynomial Regression and ML Gradient Boosting. In Hynes Convention Center. MIT Sloan Sport Analytics Conference 2024 Research Paper Competition. MIT Sloan School of Management.
• Geise, H. et al., 2024. Partner Effects and Performance: Exploring Pairing Dynamics in Professional Golf. In The Midwest Sport Analytics Meeting. Central College.
• Ehrlich, J. et al., 2024. Analyzing Golf Swing Variance: Unraveling its Impact on Strokes Gained. In Loughborough University. 11th World Scientific Congress of Golf.

Consulting

• Cap Patrol. I helped Cap Patrol by creating a new algorithm for detecting "sandbaggers," which are golfers who inflate their handicap in order to win at "net" events. I also created a machine learning model for estimating the correct handicap to use in the event of a golfer being flagged as a "sandbagger."

Active Service

Professional Service

• Reviewer/Referee, Journal of Sports Sciences, Reviewed: Comparison of Three Launch Monitors Assessment of Driver Performance Ref.: Ms. No. RJSP-2024-2321. (active since: 2025)

Public

• Member, OpenAI Community Forum, The OpenAI Forum community aims to build an ecosystem of collaborators that help us achieve our mission of building AGI that benefits all of humanity.. (active since: 2024)

Honors, Awards, and Recognition

• 2025 Research Paper Winner, MIT Sloan Sports Analytics Conference
• 2024 Research Paper Finalists, MIT Sloan Sports Analytics Conference
• Carnegie Mellon Sports Analytics Reproducible Research Competition
• WIU’s College of Business and Technology Excellence in University/ Community Service
• WIU’s College of Business and Technology Excellence in Teaching with Technology
• WIU’s Provost’s (University level) Award for Academic Excellence in Teaching with Technology
• WIU's School of Computer Science's Graduate Teacher of the Year
• WIU's School of Computer Science's Undergraduate Teacher of the Year

Memberships

• OpenAI Forum. The OpenAI Forum is a new initiative that brings together domain experts and students to discuss and collaborate on the present and future of AI. The Forum features events such as in-person meet-ups highlighting technical talks, dinner-mixers at OpenAI, educational webinars and expert roundtable conversations, and plenty of opportunity for members (including OpenAI researchers) to network and cross pollinate ideas. Forum programming will be co-created by community members, and facilitated by OpenAI.The OpenAI Forum community aims to build an ecosystem of collaborators that help us achieve our mission of building AGI that benefits all of humanity. Criteria to Join: Demonstrated interest in the intersection of applicant domain of expertise and AI.The ability to make a time commitment to participate in 1 hour worth of activities per fiscal quarter.Demonstrated expertise in your professional field or academic discipline.Applications will be considered on a rolling basis. We aim to keep Forum engagement opportunities meaningful and intimate, and inclusive of a diverse array of perspectives.

Recent Media Mentions:

• The Ryder Cup pours millions into promoting golf. But does the sport even need saving? (26 September 2025)
• 3s aren’t everything (6 March 2024)
• Are NBA teams taking too many 3-pointers? Yes, according to two Syracuse professors (28 February 2024)