Health · pace & performance

Pace Calculator

Running, cycling or swimming — pace, percentile, and how you compare, all from one time.
pace = time / distance
Running · 5K · 25:00

Sport

Your performance

Reference times

Your result

Finish time
25:00
Pace
5:00 /km
Speed
12.0 km/h

Where you rank

Your pace, projected to other distances

Field notes

Why endurance pace isn't linear

How it works

One time, three ways to read it

Enter one finish time and this tool does three things with it. First, the basic conversion — pace, speed, and the reverse calculation, so entering a target pace instead works just as well. Second, it places your time on the real population distribution of finishers at that exact distance, modelled as a log-normal curve (the standard, well-documented shape of race-time distributions) calibrated against published average and beginner benchmarks. Third, it projects your current level to every other standard distance using an endurance fatigue exponent — 1.06 for running, the well-validated Riegel constant published in 1977 and confirmed across tens of millions of race results since; a gentler, less rigorously established estimate for cycling and swimming, disclosed as such.

Worked example

A 25:00 5K run projects, via the Riegel formula, to almost exactly 52:00 for 10K, 1:55:00 for a half marathon, and 4:00:00 for a marathon — matching the commonly-cited reference conversion for that exact 5K time. The same run sits at roughly the 75th percentile of all 5K finishers — faster than about three-quarters of everyone who lines up.

Why does the Riegel exponent only really apply to running?

It was derived from — and validated against — running race results specifically. Cycling's aerodynamic drag dominates its energy cost in a way running's air resistance doesn't, and swimming's water resistance scales differently again, so this tool uses gentler, less rigorously sourced fatigue estimates for those two sports rather than borrowing running's constant wholesale.

What does "percentile" actually mean here?

It's the estimated fraction of all finishers at that distance who are slower than your time — a 75th percentile 5K means you'd finish ahead of roughly 75% of a typical race field, based on a statistical model of the population, not a specific race's actual results.

Why do average times look slower than I expected?

Published "average" race times include the entire finisher population — first-timers, charity participants and run-walkers alongside serious amateurs — which pulls the average well below what a regularly-training recreational athlete would post.

Why does the drop-off projection get less reliable at longer distances?

Riegel's formula (and its cycling/swimming analogues here) assumes equivalent training for both distances — a fast 5K only predicts a fast marathon if the underlying endurance base actually supports it, which is why race-prediction tools are most accurate between distances that aren't too far apart.

Population estimates, not a race-specific database. Percentiles and reference times are modelled from published aggregate statistics, not a specific event's actual results — treat them as a useful reference point, not a certified ranking.