Closing the Inaccuracy Gap

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.

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