Willow Sports AI v3.11 - A New Level of Control in Motion Analysis

At Willow, we are obsessed with the feedback loop. How do we help an athlete iterate faster? How do we shorten the distance between seeing an area for improvement and internalizing the change?

The most critical moments in an athletic motion - the point of contact in a baseball swing, the transition at the top of a golf swing, the release of a pitch - often last less than a second. Reviewing them effectively has been a hard problem. The real insight is often buried in a handful of frames.

Today, we're shipping a significant update to the core Willow platform (both BigHitter and GolfLogic). We re-thought the interface from first principles, with a single goal: to give players and coaches finite, millisecond-level control over the replay of the kinematic sequence or motion phase.

What's New:

We focused on removing friction and increasing precision. The new interface provides:

• Frame-by-Frame Stepping: The new forward and backward controls move the video by a single unit of the captured frame rate. This allows for the slow, deliberate deconstruction of a motion, isolating the exact frames where mechanics break down or excel.
• Integrated Play/Pause: The primary play and pause function is now integrated directly with the stepping controls, creating a single, focused hub for motion control.
• Unobtrusive Speed Controls: The playback speed selectors are individual, transparent buttons. They provide slow-motion capability without obscuring the athlete's hands, feet, or club path at the bottom of the screen. The active speed is highlighted with a subtle, rounded overlay.
• Precision Timeline Scrubber: A full-width scrubber allows you to jump to any point within the analyzed segment.

This isn't just about adding buttons. It's about building a better tool for discovery. When you can scrub back and forth over a 200-millisecond impact phase, stepping through it frame by frame, you build a much deeper understanding of the AI's analysis. You can see the bat path deviation or the change in spine angle that the model identified.

This a better surface for human-AI collaboration. The more precisely you can see and understand the data, the more effectively you can improve. Our goal is to continue building tools that accelerate that process.

Check it out:

We believe this new level of control will unlock a deeper understanding for players and coaches. We can’t wait to see how you use it.

— The Willow Sports AI Team