Project 4:05: Optimizing USA Cycling’s Women’s Team Pursuit Gold

Ryan Cooper (), Lindsay Golich (), Craig Griffin (), Jono Hailstone (), Jim Miller () and Gary Sutton ()
Additional contact information
Ryan Cooper: USA Cycling, Colorado Springs, Colorado 80919
Lindsay Golich: U.S. Olympic & Paralympic Committee, Colorado Springs, Colorado 80909
Craig Griffin: USA Cycling, Colorado Springs, Colorado 80919
Jono Hailstone: USA Cycling, Colorado Springs, Colorado 80919
Jim Miller: USA Cycling, Colorado Springs, Colorado 80919
Gary Sutton: USA Cycling, Colorado Springs, Colorado 80919

Interfaces, 2026, vol. 56, issue 1, 5-22

Abstract: In Olympic cycling, the difference between earning a gold medal and not earning a medal is measured in fractions of a second. For USA Cycling’s women’s team pursuit squad, the 2023 World Championships in Glasgow, Scotland, highlighted a stark reality: the team placed sixth with a time of 4:12.684 and missed the qualification round for the bronze medal by 0.159 seconds. With the Paris 2024 Olympics approaching and the team falling to eighth place in the world ranking, the challenge was clear: reduce nearly seven seconds off the team’s performance in one year, setting an ambitious target of 4:05 for the gold. With limited funding compared with powerhouse nations such as Great Britain, Australia, and New Zealand, USA Cycling relied on operations research, machine learning, data analytics, race simulation, and targeted athlete development to bridge the gap. Armed with cutting-edge analytics and modeling, real-time performance tracking, and aerodynamic innovations, Project 4:05 aimed at optimizing every aspect of the team’s race preparation and strategy from initial goal setting to team selection to race day tactical planning. Through data-driven decision making, USA Cycling achieved what few thought was possible: a stunning eight-second reduction in time to capture Olympic gold with a time of 4:04.306.

Keywords: Edelman Award; operations research; optimization; mixed-integer programming; sports analytics; Olympic cycling; team pursuit; aerodynamics (search for similar items in EconPapers)
Date: 2026
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