Design and Product Development

Grading Runners: A Pilot Study to Reverse Engineer Patterns to Understand the Sizing of a Population 

Authors: Susan L Sokolowski (University of Oregon) , Jacob Searcy (University of Oregon) , Anish Dulal , Chris Stone , KJ Fightmaster

Abstract

In the sports product industry, accurate apparel sizing is important for performance, yet traditional pattern grading methods rely on linear regression measurement assumptions that may not reflect real-world body diversity. This research investigates whether a dataset of 3D body scans of runners can depict improved approaches to grading and sizing athletic tights for male and female runners.

Keywords: Grading, Runners, Patternmaking, Machine Learning

How to Cite: Sokolowski, S. L. , Searcy, J. , Dulal, A. , Stone, C. & Fightmaster, K. (2025) “Grading Runners: A Pilot Study to Reverse Engineer Patterns to Understand the Sizing of a Population ”, International Textile and Apparel Association Annual Conference Proceedings. 1(1). doi: https://doi.org/10.31274/itaa.21754