Show Notes
In this episode of the Science for Sport Podcast, host Richard Graves is joined by Jordan Lucier, Senior Director of Engineering at Catapult and Co-Founder of Perch, to explore the next evolution of performance monitoring in the weight room.
Perch has become one of the most widely used camera-based systems for measuring barbell velocity and strength training performance in elite sport. Now, with the launch of Perch P2, the technology is taking another step forward.
Jordan shares the story behind the development of Perch, how computer vision and machine learning are used to quantify weightlifting performance, and why the weight room has historically been one of the least measured environments in sport.
The conversation explores the key technological advancements behind P2 — including improved camera technology, greater processing power, enhanced portability, and new possibilities for tracking movement quality and technique.
Jordan also discusses how better strength training data can help coaches build a more complete picture of athlete performance, how Perch fits alongside Catapult’s wider ecosystem of athlete monitoring tools, and why the next frontier may lie in connecting weight room insights with on-field performance.
In this episode you will learn
How Perch evolved from an early idea into a leading weight room monitoring system
Why velocity-based training has become increasingly important in elite sport
How computer vision technology can quantify barbell movement and lifting performance
The key upgrades introduced with the new Perch P2 system
Why portability is a major step forward for strength and conditioning environments
How improved frame rates and camera technology increase measurement accuracy
The concept of the “inaccuracy gap” and why it matters for explosive movements
How machine learning is used to track movement and analyse lifting performance
Why movement quality may become the next frontier of strength training analytics
How weight room data could integrate with broader athlete monitoring systems
About Jordan Lucier
Jordan Lucier is the Senior Director of Engineering at Catapult and Co-Founder of Perch, a computer vision system designed to measure performance in the weight room.
Originally developed at MIT, Perch uses advanced camera technology and machine learning to automatically track barbell velocity, movement patterns, and strength training performance without requiring wearable sensors.
Jordan has led the engineering development of the system from its early concept through to global adoption across professional teams, collegiate programmes, and high-performance environments.
His work sits at the intersection of sports science, computer vision, and performance technology, helping practitioners bring objective measurement to one of the most important areas of athlete development: strength training.
FREE 7d SCIENCE FOR SPORT ACADEMY TRIAL
SIGN UP NOW: https://bit.ly/SFSepisode241
Learn Quicker & More Effectively
Optimise Your Athletes' Recovery
Position Yourself As An Expert To Your Athletes And Naturally Improve Buy-In
Reduce Your Athletes' Injury Ratese
Save 100's Of Dollars A Year That Would Otherwise Be Spent On Books, Courses And More
Improve Your Athletes' Performance
Advance Forward In Your Career, Allowing You To Earn More Money And Work With Elite-Level Athletes
Save Yourself The Stress & Worry Of Constantly Trying To Stay Up-To-Date With Sports Science Research
More from Science for Sport Podcast
Does the way we talk about aerobic and anaerobic training help us prescribe better conditioning, or can it lead us towards the wrong sessions?
Can athletes learn to grow from pressure, rather than simply recover from it?
What can a saliva sample tell a performance team that a blood test taken a few times a season might miss?
How much does the surface beneath an athlete’s feet really affect performance and injury risk?
Few people are better placed to chart the evolution of sports science in professional football than Simon Grayson.