How to read a suspension travel histogram

A suspension travel histogram plots position across the stroke on one axis and the share of the run spent there on the other. Read it by finding where the tallest part sits: a peak near dynamic sag means the spring is carrying the rider, and a spike against the end of the stroke means it is not.

Published

The position distribution panel in the BYB Telemetry software, showing median, peak and 95th percentile figures for front and rear beside an area chart of wheel travel
One run, 156,000 samples: front and rear share a 30% median, but the front peaks at 31% of wheel travel where the rear peaks at 25% — the 6-point delta the panel reports.

What a suspension travel histogram shows

Travel histogram
A chart of suspension position against time spent there: each column is one band of the stroke, and its height is the share of the run the suspension spent inside that band.
A bar chart of front suspension position, with one column per band of wheel travel from zero to one hundred percent
The same distribution drawn as columns. The tallest sit between 25% and 30% of wheel travel, and the tail runs out before 90% — this fork never reached the end of its stroke.

Tall columns are the positions the suspension used most, so the horizontal position of the peak is the first thing to read. Everything else — the width of the shoulder, the length of the tail, a spike at the far right — is read against it.

How the data behind the histogram is recorded

Linear sensors on the fork and shock measure shaft position, sampled at 500 Hz on Telemetry V3 and 1000 Hz on Telemetry V3 Pro. The software converts shaft movement to wheel travel using the frame's leverage ratio, which is why the axis reads in wheel travel rather than in shaft millimetres.

A histogram is therefore a summary and not the recording. It discards time entirely — two runs with identical histograms can feel completely different — which is what makes it good at answering where the suspension lived and useless at answering when. Data acquisition covers what else the same file holds.

What the shape of the histogram means

  • A peak near dynamic sag, around 25% to 30% of travel: the spring rate is carrying the rider and the chassis is supported
  • A peak past 50%: the setup is riding deep in the stroke, which points at a spring that is too soft
  • A peak below 20%: the setup is riding high and is not using the travel available
  • A spike hard against 100%: repeated bottom-outs, which a longer tail alone does not indicate
A position distribution chart whose front and rear traces both peak close to twenty-five percent of wheel travel and decay smoothly toward the end of the stroke
A distribution doing what it should: the peak sits near 25% of wheel travel, the shoulder is wide rather than spiked, and the tail thins out instead of stopping short or piling up at the end.

Reading front and rear together

One end of the bike is only half the answer. Overlaying the front and rear distributions shows whether the two ends are sharing the work, and a mismatch is visible as a gap between the two peaks rather than as a fault in either one.

Two overlaid distributions that track each other closely, annotated with a rear peak at twenty-five percent and a front peak at twenty-seven percent
Balanced: the software marks the rear peak at 25% and the front at 27% of wheel travel, and the two curves stay within a couple of points of each other the whole way down.
Two distributions plotted in millimetres whose peaks are far apart, the rear concentrated low in its stroke and the front spread much further
The same overlay when the two ends disagree, here in millimetres: the rear peaks near 20 mm and is finished before 75 mm, while the front peaks near 45 mm and carries past 150 mm.

How many runs before a histogram means anything

A histogram is a count, so its shape is only as trustworthy as the number of samples behind it. The panel above reports 156,000 samples; a short section of trail at 1000 Hz gives a few thousand, and that is enough to show a shape but not enough to settle a setting.

Two runs that BYB Tech recorded make the point: 8,212 samples over 8.2 seconds of Livigno, and 11,020 samples over 11.0 seconds of a supercross track. Both draw a clean distribution. Neither is a diagnosis, because eleven seconds of one rider on one section is not the ride.

The method that does work is a controlled comparison. Ride the same section at the same effort, change one thing, ride it again, and compare the two histograms against each other rather than against an ideal shape.

Common questions

What does a good travel histogram look like?
A single peak near dynamic sag, roughly 25% to 30% of travel, with a wide shoulder and a tail that thins out toward the end of the stroke. What it should not have is a second peak, or a spike against 100%.
What causes twin peaks in a travel histogram?
Two peaks usually mean the run contained two different kinds of riding — a smooth section and a rough one, or a climb and a descent — rather than one setup fault. Splitting the run by section before reading it is the fix.
How many runs do you need before the data is reliable?
Enough samples that the shape stops changing when you add more. One short section at 1000 Hz gives a few thousand samples and a shape that moves run to run; a full session gives six figures and a shape that holds.