Four recent alumni and a current student are co-authors of a book chapter, “Using Data and Sports Equipment Technology to Predict Athletic Performance.”

Published on April 8 in The Handbook of Visual, Experimental, and Computational Mathematics, the chapter includes data analytics research by five students of Dr. Ryan Savitz: alumni Andrew Bjorkelo, Helen Cooney, Ollie DiDonato, and Christopher Greve and current student Caley Gee.

The aim of the chapter, according to an abstract by publisher Springer Nature is “to present a review of how performance data, as well as knowledge of the type of sports equipment technology employed, can be used to predict athletic performance.”

The chapter focuses on ice hockey, karate, field hockey, baseball, and track and field. It also takes a brief look at how the use of a specific type of sports equipment (carbon-plated running shoes) can be used to predict improvement in performance in marathon races.

"These co-authors are an all-star team of NU math and sport management majors,” says Savitz. “The research we have done has spanned several years, and some of the students had the opportunity to work with prominent scholars from other universities. The experience has also been great fun for me. I got to spend time doing statistics and talking sports with our students, which is about as good as it gets in my book."

In addition to the student/alumni authors, three faculty members contributed to the chapter: Neumann’s Savitz, Bo Wagonner of the University of Colorado, and Jared Ward of Brigham Young University.