Overview
Running pace — the time it takes to cover one kilometre or one mile — is the single number that connects training plans, race goals, and finish-time predictions. Whether you are checking a recent 5K result, planning splits for a marathon, or converting a treadmill's speed display into a number that matches your usual training log, the underlying math is the same simple relationship between time and distance.
This guide covers calculating pace from a finish time, converting a target pace into an expected finish time, switching between per-kilometre and per-mile pace, and using Riegel's formula to predict performance at a new distance from a recent result. Use the Pace Calculator to run these conversions instantly once you understand how each one works.
What You Need
Before calculating pace, gather:
- Total time for a run or race, in hours, minutes, and seconds
- Distance covered, in kilometres or miles (be precise — a "5K" road race may not be exactly 5.00 km depending on the course)
- Target pace or target finish time, if you are working backward from a goal rather than forward from a completed run
- A recent race result (distance and time), if you want to predict performance at a different distance
Step 1: Understand Pace vs Speed
Pace is time per unit of distance — minutes and seconds per kilometre or per mile. Speed is distance per unit of time — kilometres per hour or miles per hour. The two describe the same underlying effort but are calculated in opposite directions, and runners generally find pace more intuitive because race goals are almost always stated as a target time over a known distance, not a speed.
Pace = Time ÷ Distance
Speed = Distance ÷ Time = 1 ÷ Pace (with unit conversion)
Treadmills and cycling computers typically display speed rather than pace, which is why runners training primarily outdoors sometimes need to convert a treadmill's km/h reading into the per-kilometre pace they are used to seeing on race results.
Step 2: Calculate Pace from Time and Distance
This is the most basic and most frequently needed calculation — converting a finish time into a pace per kilometre or per mile.
Pace = Total Time ÷ Distance
Worked example: A runner finishes a 5K (5 kilometres) in 25 minutes.
Pace = 25 minutes ÷ 5 km = 5:00 per km
Worked example with a less round number: A runner finishes a 10K (10 kilometres) in 52 minutes 30 seconds.
Total time in minutes = 52.5
Pace = 52.5 ÷ 10 = 5.25 minutes per km = 5:15 per km
When your finish time includes seconds that do not divide evenly, convert to decimal minutes first (30 seconds = 0.5 minutes) before dividing, then convert the decimal result back to minutes and seconds at the end.
Step 3: Calculate Finish Time from Target Pace
Runners planning a race often work in the opposite direction — starting from a target pace and calculating the expected finish time over the full race distance.
Time = Pace × Distance
Worked example: A runner targets a 5:30 per kilometre pace for a full marathon (42.2 km).
Pace in decimal minutes = 5.5
Time = 5.5 × 42.2 = 232.1 minutes
Convert to hours: 232.1 ÷ 60 = 3.87 hours = 3 hours 52 minutes
This calculation is the basis for setting mile or kilometre splits during a race — multiply the target pace by each successive distance checkpoint (5 km, 10 km, half marathon point, and so on) to get a target split time at each checkpoint, which is far more useful during a race than only knowing the final target time.
Step 4: Convert Between Pace Units (Per Km vs Per Mile)
Race results, training apps, and watches do not consistently use the same unit, so converting between per-kilometre and per-mile pace is a frequent need.
Pace per mile = Pace per km × 1.60934
Pace per km = Pace per mile ÷ 1.60934
Worked example: A pace of 5:00 per kilometre converts to per-mile pace.
5:00 = 5.0 decimal minutes
5.0 × 1.60934 ≈ 8.05 minutes = 8:03 per mile
Worked example in the other direction: A pace of 8:00 per mile converts to per-kilometre pace.
8:00 = 8.0 decimal minutes
8.0 ÷ 1.60934 ≈ 4.97 minutes = 4:58 per km
Because a mile is longer than a kilometre, per-mile pace will always be a larger number (more minutes) than the equivalent per-kilometre pace for the same actual running speed — this is a useful sanity check if a conversion produces a smaller per-mile number, which signals the multiplication and division were swapped.
Step 5: Predict Race Pace from a Recent Result
Riegel's formula estimates how a known time over one distance translates into an expected time over a different distance, accounting for the fact that endurance demands grow faster than distance alone would suggest.
T2 = T1 × (D2 / D1)^1.06
Where T1 is your known time, D1 is the known distance, D2 is the target distance, and T2 is the predicted time at the target distance.
Worked example: A runner recently completed a 10K in 50 minutes and wants to predict marathon (42.2 km) finish time.
T2 = 50 × (42.2 / 10)^1.06
T2 = 50 × (4.22)^1.06
T2 = 50 × 4.61
T2 ≈ 230.5 minutes ≈ 3 hours 50 minutes
Once you have the predicted total time, divide by the marathon distance to get the predicted pace: 230.5 ÷ 42.2 ≈ 5:28 per kilometre. This prediction assumes equivalent training and conditions between the 10K and the marathon — it is a reasonable planning estimate, not a guarantee, especially as the gap between the known and target distance grows larger.
Common Mistakes to Avoid
Confusing pace and speed on a treadmill. Treadmill displays typically show speed in km/h or mph, not pace in minutes per kilometre. Comparing a treadmill's "12" reading directly against your usual "5:00 per km" training log entry is comparing two different kinds of numbers — convert the treadmill speed to pace first (60 ÷ speed in km/h = pace in minutes per km) before making any comparison.
Not accounting for terrain and elevation when predicting race pace. Riegel's formula and basic pace calculations assume flat, comparable terrain. A 10K time set on a hilly trail course will predict a faster flat-marathon time than is realistic, because the hilly course demanded more effort per kilometre than a flat one would. Treat predictions across very different terrain as rough estimates and adjust downward in expected pace if the target race has significant elevation gain.
Using linear scaling instead of Riegel's exponential formula. Simply multiplying a 10K pace by the marathon distance (linear scaling) overestimates marathon performance, because it ignores the additional fatigue that accumulates over a much longer distance. The 1.06 exponent in Riegel's formula specifically corrects for this non-linear slowdown — skipping it produces an overly optimistic finish time prediction that is very difficult to actually achieve on race day.
Formula & Methodology
The two foundational formulas for pace work in opposite directions from the same relationship:
Pace = Time ÷ Distance
Speed = Distance ÷ Time = 1 / Pace (with appropriate unit conversion)
Both formulas describe the same physical effort; the choice of which to use depends on whether your goal or your known data is stated as a time-per-distance figure (pace) or a distance-per-time figure (speed).
Riegel's Race Time Prediction Formula extends this basic relationship to handle performance across different distances:
T2 = T1 × (D2 / D1)^1.06
The exponent of 1.06, rather than 1.0, is the key feature of this formula. An exponent of exactly 1.0 would assume pace stays perfectly constant regardless of distance — in other words, that a runner could sustain their 10K pace all the way through a marathon, which is physiologically unrealistic for almost all runners due to glycogen depletion, cumulative muscular fatigue, and the cardiovascular demands of sustained effort over several hours. Pete Riegel derived the 1.06 value empirically from large datasets of real race results across many distances and ability levels, and it has remained a reasonably reliable predictor across decades of subsequent use.
The formula is most accurate when D1 and D2 are not too far apart — predicting a half marathon from a 10K result is generally more reliable than predicting a full marathon from a 5K result, since smaller extrapolations carry less compounding error from the exponent. For best results, use the most recent comparable-distance race result available, run under conditions (weather, terrain, training state) similar to those expected on the target race day.