Race Time Predictor: How Riegel's Formula Works
The math behind race time prediction from a known result, why the formula isn't linear, and how accurate it actually is.
Predicting a marathon time from a 5K result sounds like it should be simple multiplication — but runners reliably slow down at longer distances, so an accurate predictor has to account for that fatigue effect rather than assuming a flat pace holds forever.
Riegel's formula
T2 = T1 × (D2 / D1)^1.06
Published by Peter Riegel in 1977 and still the standard method behind most race-time predictors, this formula uses an exponent slightly above 1.0 to model the realistic slowdown that happens as distance increases — a pure linear scale-up (exponent = 1.0) would predict times that are too fast at longer distances.
Worked example: from a mile time
| Reference | Predicted |
|---|---|
| 1 mile in 9:00 | 5K: 29:56 |
| 1 mile in 9:00 | 10K: 1:02:24 |
| 1 mile in 9:00 | Half marathon: 2:17:41 |
| 1 mile in 9:00 | Marathon: 4:47:04 |
Where the prediction breaks down
- It assumes similar training and pacing discipline across distances — a 5K specialist without endurance base will run slower than predicted at a marathon.
- Weather, terrain, and course elevation aren't factored in at all.
- Predictions from a very short reference distance (like a single mile) are generally less reliable than predictions from a longer, race-specific effort.
Use the Running Pace Calculator with your most recent race or time-trial result for the most reliable prediction available from this method.