Race Predictor: Running Time Calculator
Enter a recent race distance and finish time to predict your time for any other distance, from a 5K to a full marathon. The calculator uses Peter Riegel's widely validated formula and shows your predicted pace per kilometre and per mile for each target distance. Results update instantly as you type.
Formula
Worked example
A runner finishes a 10K in 48:30 (2910 s). Predicted marathon time: 2910 x (42195 / 10000)^1.06 = 2910 x 4.2195^1.06 = 2910 x 4.656 = 13,549 s = 3:45:49. Required pace: 13,549 / 42.195 = 321.1 s/km = 5:21 per km.
What the Riegel formula is and where it comes from
The race predictor uses the Riegel formula, published by Peter Riegel in Runner's World in 1977 and later refined in a 1981 American Scientist paper. Riegel studied how running pace declines as distance increases and found a consistent power-law relationship: T2 = T1 x (D2 / D1)^1.06. The exponent 1.06 captures the fact that your average pace slows down by roughly 6 percent every time the race distance doubles. The formula holds well for efforts lasting roughly 3.5 minutes to about 4 hours, which covers everything from a fast mile to a marathon for most recreational runners.
How to use this calculator
Enter the distance and finish time of a race you have already completed - ideally from the last four to six weeks, and ideally at a similar intensity to the one you are targeting. Then select the distance you want to predict. The calculator instantly shows your predicted finish time, your required pace per kilometre and per mile, and a full breakdown table covering all standard distances from 1 mile to marathon. Switch the distance unit between kilometres and miles to match your training logs. For custom distances such as a trail race or a time trial, choose "Custom distance" from either dropdown.
When the prediction is most and least accurate
The Riegel formula is most reliable when the two distances are reasonably close together, for example predicting a 10K from a 5K, or a half marathon from a 10K. Accuracy drops when you jump many multiples in distance, especially upward: predicting a marathon from a 5K reference tends to be optimistic because the marathon demands specific aerobic base, pacing discipline and glycogen management that a short-distance effort does not test. Research published since 2010 has confirmed that for distances beyond the half marathon, Riegel's exponent slightly underestimates how much pace declines, so the predicted marathon time may be a little fast for many runners. Use the prediction as an informed starting point and adjust based on your training volume.
What affects your actual race time beyond the formula
The Riegel formula treats running performance as a pure physiological curve with no external variables. In reality, your finish time is also shaped by weather (heat and humidity slow you more at longer distances), course profile (hills add time that flat predictions miss), race-day execution (pacing strategy, fuelling and hydration), training specificity (mileage for the target distance matters enormously), and rest and recovery in the week before the event. A runner who has done consistent long runs for a marathon will outperform the Riegel prediction compared with one who simply extrapolates from 5K speed work. Treat the output as a goal bracket rather than a guaranteed result.
Standard race distances and typical finish times
| Distance | Beginner | Recreational | Competitive | Elite (approx.) |
|---|---|---|---|---|
| 5K | 35-45 min | 25-35 min | 18-25 min | Under 14 min |
| 10K | 70-90 min | 50-70 min | 36-50 min | Under 28 min |
| Half Marathon | 2:30-3:15 | 1:50-2:30 | 1:20-1:50 | Under 1:01 |
| Marathon | 5:00-6:30 | 3:45-5:00 | 2:45-3:45 | Under 2:05 |
Approximate finish times for recreational, competitive and elite runners at common distances.
Frequently asked questions
Which formula does this race predictor use?
This calculator uses the Riegel formula: T2 = T1 x (D2 / D1)^1.06. Published by Peter Riegel in 1977, it is the most widely used race prediction formula and the basis for many running apps and training tools. The exponent 1.06 reflects the empirical observation that pace declines by about 6 percent each time the race distance doubles.
How accurate is the Riegel formula?
The formula is quite accurate for predicting times between distances within a factor of roughly two or three, for example 5K to half marathon or 10K to marathon. For very large jumps in distance the prediction tends to be slightly optimistic, especially for the marathon, where specific long-run training matters in ways the formula cannot capture. Most runners find the prediction within a few percent when they are well trained for the target distance.
Can I use a training run instead of a race time?
You can, but the prediction will be less reliable. Race times reflect maximum effort in race conditions. Training runs are usually at a lower intensity, so entering a training pace will produce an optimistic prediction. If you use a training effort, consider a time trial at genuine race effort rather than a typical easy or tempo run.
Why does the marathon prediction seem fast?
This is a known limitation of the Riegel formula for very long distances. The exponent 1.06 was calibrated on data that skews toward elite and sub-elite runners who maintain their pace ratio across distances better than recreational runners. If you are newer to marathon distance or have not done sufficient long runs, your actual time is likely slower than the prediction. Adding 5 to 10 minutes to the predicted marathon time is a common rule of thumb for less experienced runners.
What is the best input race to predict a marathon time?
A half marathon run within 6 to 8 weeks of your target marathon, at full race effort, gives the most accurate prediction. A 10K also works well. Shorter races such as a 5K are further from the marathon in physiological demand, so the extrapolation is less precise, but still better than no data at all.
Does the calculator work for ultramarathon distances?
The Riegel formula loses accuracy beyond marathon distance because fatigue, sleep deprivation, and walking breaks play a large role in ultra performance that no pace-based formula captures. For ultramarathons, race-specific experience and course knowledge are more reliable guides than any formula.