Race Time Predictor

How accurate is the race predictor?

The Riegel formula is most accurate when predicting across similar distances (e.g., 5K to 10K, or 10K to half marathon). Accuracy decreases significantly when extrapolating across very different distances — particularly from short to ultra distances. Factors like pacing, nutrition, and terrain can cause real performances to deviate by 5–15% from predictions.

What is the Riegel formula?

The Riegel formula, published by Pete Riegel in 1977, states: T2 = T1 × (D2 / D1)^1.06. The exponent 1.06 reflects the empirical observation that performance degrades slightly faster than a linear relationship with distance — running a race twice as long takes more than twice as long. It's the most widely used race prediction formula.

Does the formula work for ultramarathons?

Not reliably. The Riegel formula was derived from road race data in the range of 1 mile to marathon. For ultras (50K+), fatigue, sleep deprivation, elevation, and nutrition strategy have outsized effects that the formula doesn't account for. Use ultra predictions as a very rough baseline only.

How can I use race prediction in training?

Use predicted times to set realistic goals for target races, to design interval training paces (e.g., target 5K pace for track work), and to assess whether a goal race time is achievable given your recent fitness. Re-calculate predictions after key training races to track fitness improvements.

What affects race performance beyond fitness?

Weather (heat and humidity can slow marathon times by 5–10%), course elevation, race-day fuelling, tapering quality, pacing strategy, sleep, and experience all play significant roles. The formula predicts 'equivalent effort' times under ideal conditions — real-world races rarely match those conditions exactly.