How to analyze alpine ski racing performance with video and GPS data

In alpine ski racing, good video review is often limited by one problem: you can see tactics and technique, but you cannot measure the impact with confidence. GPS athlete data fills that gap. When video and data are linked, you can move from “that looked fast” to “this is where time changed, and this is what caused it” across slalom, giant slalom, Super-G, and downhill.

This article is a high-level workflow for performance review. For a deeper explanation of what GPS measures (and what it does not), read GPS ski analysis explained for coaches.

Why video alone is not enough in ski racing

Video is still the most important tool for seeing how an athlete skis. It shows timing, stance, line choice, and how an athlete responds to terrain and course setting. The limitation is precision.

• Video shows movement, not magnitude. You can often spot where an athlete looks late, tight, or over-turned, but it is hard to tell if the cost was small or decisive.
• Single-run review lacks context. Even experienced coaches can struggle to judge a run in isolation. Without an objective reference, it is easy to over-weight what is visually obvious.
• Video file management becomes real overhead. If video is not consistently labeled by athlete and run, coaches often lose time searching, rewatching, and sorting instead of reviewing.

What GPS athlete data adds to race analysis

GPS athlete data adds objectivity to video. It gives you a measurable signal that you can attach to a moment on snow. When it is linked to video, you can see the action and the impact together.

• Every frame has performance context. Instead of guessing whether a tactical choice cost time, you can see how speed, time progression, acceleration, and lateral force change through the run.
• You can compare against a reference. With the right comparison reference (fastest overall, fastest for a run number, or an athlete’s best run), you can quickly see where performance was ahead or behind.
• Data makes the “where” obvious. Because the data is tied to location on the hill, you can identify where a change happened, then use video to understand what the athlete did to create it.

If you want a clearer overview of what “linked video and data” looks like in practice, see the data-linked video analysis capability.

Linking video and data during review

Linking video and data is not only about deeper analysis. It also changes how quickly you can get to the right moments.

• Less manual prep. When video is tied to athlete identity, sessions, and runs, you reduce time spent labeling and organizing clips.
• More review time, not more admin. Capturing more video does not have to double the workload if the system keeps it organized and searchable.
• Better continuity over a season. When the same review structure is used all year, comparisons become easier and feedback becomes more consistent.

If you want the full end-to-end workflow that many teams use day to day, start here: How Protern Works.

Identifying where time was gained or lost

The fastest way to improve review quality is to stop scrubbing video blindly. Use the chart for the run to identify where performance changed, then go to the video at that moment.

• Use peaks, dips, and sustained trends. A short dip can signal a mistake. A sustained change often signals a tactical or technical pattern worth addressing.
• Use colour cues to prioritize. If your comparison reference highlights where the athlete was clearly ahead or behind, you can go straight to the most meaningful sections.
• Jump to the setup, not the result. When you navigate from a chart, go to the moment just before the change begins. That is usually where the decision or setup happened.

When you are ready to go deeper into side-by-side review mechanics and comparison modes, use how to compare ski runs using video and GPS data.

Explaining performance clearly to athletes

Many athletes struggle to connect a coach’s feedback to what they feel on snow. Video helps, but the addition of data can make cause and effect easier to understand.

• It turns feedback into evidence. If a coach points out a tactical issue, seeing the performance change on the chart reinforces the message.
• It supports athlete-driven learning. Athletes can review their own runs and see patterns without needing a coach beside them for every clip.
• It reduces misinterpretation. Video can look “good” while performance drops, or look “messy” while performance improves. Data helps keep the conversation grounded.

For discipline-specific examples, especially around rhythm, combinations, and acceleration timing in slalom, read what coaches should look for in slalom video and GPS data review.