What is a race time predictor?
A race time predictor estimates your expected finish time for a target race distance based on a result from a previous race. It applies the Riegel formula — a power-law equation developed by American engineer Peter Riegel in 1977 — to scale your known performance across different distances. Runners use it to set realistic goals, choose target paces, and plan race strategy. Use it alongside the running pace calculator to convert your predicted time into a per-kilometre target pace.
How do you predict race finish time?
Enter a race you have already completed — the distance and your finishing time — then select the target distance you want to predict. The calculator applies the Riegel formula to estimate how long the new distance should take at a comparable effort level. For best results, use a recent race run at full effort under normal conditions.
What is the Riegel formula?
The Riegel formula is: T2 = T1 × (D2 ÷ D1)1.06
Where T1 is your known race time (in seconds), D1 is the known distance, D2 is the target distance, and T2 is the predicted finish time. The exponent 1.06 is the fatigue factor — it accounts for the fact that running slows disproportionately as distance increases. A perfect linear scaling would use 1.0; the 0.06 premium captures the cumulative effect of fatigue over longer efforts.
What are some race time prediction examples?
5K in 25:00 → 10K prediction: T2 = 1500 × (10 ÷ 5)1.06 = 1500 × 2.085 ≈ 3127 s = 52:07
10K in 50:00 → Half marathon prediction: T2 = 3000 × (21.1 ÷ 10)1.06 ≈ 3000 × 2.24 ≈ 6720 s = 1:52:00
Half marathon in 1:45:00 → Marathon prediction: T2 = 6300 × (42.195 ÷ 21.0975)1.06 ≈ 6300 × 2.085 ≈ 13136 s = 3:38:56
Pair predicted times with the calories burned calculator to estimate your energy expenditure for the race.
When is a race time predictor useful?
Race time predictors are most useful for setting goal paces before a new distance, qualifying for events with time standards, choosing the correct starting corral, and structuring training blocks. They give a data-driven starting point rather than guessing based on feel.
How accurate is the Riegel formula?
The formula is most reliable when predicting between distances that are close in length — for example, from a 10K to a half marathon. Accuracy decreases significantly for marathon and ultramarathon predictions, where the Riegel formula tends to be optimistic (too fast) by 10 minutes or more. High training mileage, race-day conditions, course elevation, and heat all affect actual performance beyond what the formula captures. Use the prediction as a guideline rather than a guarantee, and validate against a TDEE calculator to ensure your nutrition strategy matches your expected effort.
Does the Riegel formula work for all types of runners?
The formula is best suited to endurance-trained runners who race regularly across similar distances. Sprinters and speed specialists tend to get pessimistic predictions for longer distances because their muscle fibre composition favours power over sustained aerobic output. Ultra-distance runners may see overly optimistic predictions, as the formula cannot account for the extreme cumulative fatigue of multi-hour efforts beyond the marathon. For the most accurate result, use a recent race run at close to maximum effort — ideally at a distance not too far from your target race.