Dr. Stephanie Kovalchik

Dr. Stephanie Kovalchik, is currently a Research Fellow within ISEAL (International Social and Environmental Accreditation and Labelling Alliance) and holds a joint appointment at Tennis Australia, where she works as a data scientist for the Game Intelligence Group.

Stephanie’s area of expertise is statistics. She received her PhD from UCLA, where she focused on multi-level modelling, prediction, and risk assessment. Stephanie has held appointments as a statistical researcher at the National Cancer Institute and the RAND Corporation, where she developed new statistical methods for handling complex health science data.

While working in the health sciences, Stephanie was also conducting quantitative research in tennis. In her current role at ISEAL and Tennis Australia, she is working on advancing tennis analytics. She is involved with various projects using data analysis to help understand performance in tennis and has particular interest in identifying patterns of performance, patterns of development and measuring the mental side of tennis. She is also the creator of the tennis analytics blog On The T and regularly writes on tennis on twitter @StatsOnTheT.

Education:

BSc, Cal Tech

MSc, UCLA

PhD, UCLA

Areas of Expertise:

Measurement theory in sport

Performance analysis

Prediction

Sports performance analytics

Statistical modelling

Publications:

Author, "Is there a Pythagorean theorem for winning in tennis?" Journal of Quantitative Analysis in Sport. (In press)

 Author, "The older they rise the younger they fall: age and performance trends in men’s professional tennis from 1991 to 2012." Journal of Quantitative Analysis in Sports, 10(2), 99-107. (2014)

 Co-author, "Population-based absolute risk estimation with survey data." Lifetime data analysis, 20(2), 252-275.(2014)

 Co-author, "Longitudinal analyses of Olympic athletics and swimming events find no gender gap in performance improvement." Journal of Quantitative Analysis in Sports, 9(1), 15-24. (2013)

 Co-author, "A general binomial regression model to estimate standardized risk differences from binary response data." Statistics in Medicine, 32(5), 808-821. (2013)

Awards:

2016 - Elected to Executive Committe for 2018 Anziam Mathsport Conference

2015 - Section on Statistics in Sports, American Statistical Association, Elected 2017 Program-Chair

Website links:

Courses:
Meta Analysis In R

Instructor at Statistics.com since July 2016