Question 1

How accurate is the Riegel formula?

Accepted Answer

For well-trained runners racing between 5K and marathon distances, the Riegel formula is typically accurate to within 2-3%. Accuracy decreases when extrapolating across large distance differences (e.g., predicting a marathon from a 5K) or for runners who are specifically trained for one distance.

Question 2

Can I predict ultra marathon times from a marathon result?

Accepted Answer

Ultra predictions are less reliable because factors like nutrition, sleep deprivation, terrain, and mental endurance play larger roles beyond the marathon distance. The calculator shows a wider confidence range for ultra predictions to reflect this uncertainty.

Question 3

Why are my predicted times different from my actual race results?

Accepted Answer

Common reasons include: course difficulty differences (hills, altitude, weather), different levels of race-day effort, training specificity (being trained for one distance but not another), and the gap between aerobic fitness and race-specific endurance. The predictor assumes equal effort and similar conditions.

Question 4

Should I use my 5K time or my 10K time as input?

Accepted Answer

Use the race distance closest to your target prediction for best accuracy. If you're predicting a marathon time, a half marathon result will give you a more reliable estimate than a 5K. Also use your most recent result — fitness changes over time.

Question 5

What is the exponent in the Riegel formula?

Accepted Answer

The exponent is 1.06. It's the empirically fitted rate at which endurance performance degrades with distance for trained runners — Peter Riegel derived it from race-time data across running, swimming, and cycling. Because 1.06 is slightly above 1, doubling the distance more than doubles the time, which is what the formula uses to model accumulating fatigue.

Question 6

How accurate is the Riegel formula for marathon prediction?

Accepted Answer

Marathon prediction is the formula's hardest case because it sits at the far end of common race distances and depends heavily on distance-specific training. Well-trained marathoners (roughly 30-35+ weekly training miles) typically see 2-3% error, in line with the formula's general accuracy. Runners below that training volume, or finishing beyond about 4 hours, tend to run slower than the formula predicts, since it doesn't model glycogen depletion and late-race fade beyond what the 1.06 exponent already assumes.

Question 7

Can I predict a marathon time from a 10K?

Accepted Answer

Yes. A 10K-to-marathon prediction uses a distance ratio of about 4.2 (42.195km / 10km), near the edge of the formula's reliable range. Raise that ratio to the 1.06 power (≈4.600) and multiply by the 10K time: a 45:00 10K predicts roughly a 3:27:01 marathon, assuming equivalent marathon-specific training and effort.

Question 8

Where does the Riegel formula come from?

Accepted Answer

Peter Riegel published the formula in 1977 ("Time Predicting," Runner's World) and refined it in 1981 (American Scientist). It was fitted empirically to observed endurance-performance data across running, swimming, and cycling rather than derived from physiology directly, which is why the 1.06 exponent is described as a fatigue factor rather than a physical law.

Distance	D2 ÷ D1	(D2/D1)^1.06	Predicted time
10K (input)	1.000	1.000	45:00
Half marathon	2.110	2.206	1:39:17
Marathon	4.220	4.600	3:27:01

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The Riegel formula, explained

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Worked example: a 45:00 10K

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