Race Time Predictor
The Riegel model predicts race times across distances using a power-law relationship: if you know your time for one distance, you can estimate performance at any other. The formula T₂ = T₁ × (D₂/D₁)^1.06 captures how endurance declines as race distance increases. This tool extends Riegel with age-grading tables and stacks performance modifiers from every other HAM.RUN module — running economy gains, caffeine benefit, heat adaptation — into a single composite prediction.
Frequently asked questions
How accurate is the Riegel race prediction formula?
The Riegel formula is approximately 80% accurate for the general population. It tends to underpredict marathon times for recreational runners because the 1.06 exponent was derived from elite data. Recreational runners experience proportionally more fatigue at longer distances due to lower aerobic fitness and pacing errors.
How does age affect marathon performance?
Peak distance running performance is maintained until approximately age 35–40, after which a gradual linear decline occurs. The decline accelerates after age 75–78. Age-grading tables normalize performances across ages, allowing fair comparisons. A 50-year-old running 3:20 may have a higher age-graded score than a 25-year-old running 3:05.
Can I predict my marathon time from a 5K?
Yes, but with caveats. The Riegel formula provides an estimate, but marathon-specific factors (fueling, heat tolerance, training volume) create more variance at longer distances. A prediction from a half marathon result is more reliable than from a 5K. The further apart the distances, the wider the confidence interval.
Sources
- Riegel (1981). Athletic records and human endurance. American Scientist.
- Grubb (1998). Models of marathon performance. Journal of Sports Sciences.
- Tanaka & Seals (2008). Endurance exercise performance in Masters athletes: age-associated changes and underlying physiological mechanisms. Journal of Physiology.
Related glossary terms
- Riegel Model
- Joyner Model
- Compound Stress
- VO₂max