Reading step velocity, contact & flight time
What each spatiotemporal metric actually tells you about an athlete — and what to do with it.
TrackStat captures the spatiotemporal parameters of a sprint: the timing and distance of every step. On their own they’re just numbers. The skill is reading them together to understand how an athlete is moving — and what to change.
The core metrics
| Metric | What it is | Units |
|---|---|---|
| Step length | Distance covered in one step | m |
| Contact time | Time the foot spends on the ground | s |
| Flight time | Time airborne between steps | s |
| Step frequency | Steps per second | Hz |
| Step velocity | Step length × step frequency | m/s |
Step velocity is the headline
Step velocity is what wins races, and it’s the product of exactly two things:
Step velocity = step length × step frequency
That simple relationship is the whole game. A faster athlete takes longer steps, quicker steps, or both. So when you want to make someone faster, you’re really asking one question: which of those two has the most room to improve?
Contact and flight time tell you how
Two athletes can post the same step velocity in very different ways:
- Short contact, longer flight — a bouncy, elastic sprinter applying force fast.
- Longer contact, shorter flight — a more push-dominant, grinding pattern.
Neither is “wrong”, but the pattern points at the work. Long ground contacts at max velocity, for example, often point to a strength or stiffness limitation better addressed in the gym than on the track.
Putting it to work
- Establish a baseline from clean footage — filmed the way our filming guide describes, so the numbers are worth trusting.
- Read the pattern, not a single number. One step’s contact time is noise; the average across a rep is signal.
- Pick the one lever with the most room — length or frequency — and train it deliberately.
- Re-measure after the training block, marking your frames by the same rule every time, and compare.
That last step is where TrackStat earns its place: because every analysis lands on the athlete’s profile, you watch the trend across a whole season instead of arguing about one Tuesday’s numbers.