Enter a recent race or hard, measured time trial to estimate equivalent times at other distances. Use the prediction as a planning baseline, not a promise, especially when the target is much longer than the result you entered.
Race Time Calculator
Start with one recent result. Add a second result only if you want a more individualized distance-to-time model.
Add a second recent race (optional)
A second trustworthy result lets the calculator fit a simple personal power-law exponent instead of assuming the same 1.06 fatigue rate for every runner. Use results from roughly the same fitness period and comparable race effort.
Split options
How to predict a race time
Use a recent race result, choose the distance you want to predict, and start with Riegel 1.06. Predictions are most useful when the two races are reasonably close in distance and the recent result reflects your current fitness.
For a marathon or ultra, treat the number as a planning baseline. Long-run durability, training volume, fueling, pacing, course and weather become increasingly important.
On this page
How to use this race time calculator
- Use a current result: a recent race is better than an old personal best.
- Start with Riegel 1.06: it is simple and useful for race equivalency, particularly when the distances are not far apart.
- Choose a target: select one race if you want a focused prediction and splits, or show the full table.
- Add a second result only when it is trustworthy: two similar-period results can reveal whether your own endurance curve is steeper or flatter than the fixed Riegel assumption.
- Check training before adopting the goal: the formula knows your race time. It does not know your long runs, fueling or course.
Race prediction models used here
Riegel 1.06
T₂ = T₁ × (D₂ ÷ D₁)1.06
Peter Riegel’s classic model describes the relationship between performance time and distance with a power law. It is simple, transparent and still useful as a baseline.
Riegel 1.08
Uses the same equation with a larger exponent, so longer-distance predictions slow more. This is an alternate scenario, not a claim that 1.08 is the correct exponent for every recreational runner.
Cameron
The Cameron equation uses a distance-specific empirical adjustment rather than one fixed exponent. It is common in running calculators, but its original derivation is not as clearly documented in peer-reviewed literature as Riegel’s model.
Personalized two-race power law
If you enter two race results, the calculator fits the exponent that passes through those two performances. This can reflect your own speed-endurance profile better than assuming everyone has the same exponent, but only if both input races are representative.
Why the second race can help
Research using more than 1.4 million performances from over 160,000 runners found strong evidence that individual runners differ from a single universal power-law relationship. The optional second result is a simple way to capture part of that individual difference without pretending it is a full machine-learning model.
How accurate is a race time predictor?
Think of the result as an equivalent-performance estimate, not a forecast with a guaranteed error range.
- Usually more useful: 5K to 10K, 10K to half marathon, or another target not far from the input race.
- More uncertain: 1 mile to half marathon, 5K to marathon, or any prediction across very different course types.
- Marathon: recreational-runner data shows standard Riegel can be too optimistic even when shorter-race fitness is strong.
- Ultra: a simple road-race formula cannot account for terrain, climbing, hiking, aid stations, fueling or ultra-specific durability.
The original Riegel model had a practical range
Riegel described a roughly 3.5 to 230 minute “endurance range” in the original analysis. Predictions beyond that time range should be treated as extrapolation rather than as though the same relationship is guaranteed to continue indefinitely.
Example Riegel 1.06 predictions
These examples use the standard 1.06 equation and are rounded to the nearest second.
25:00 5K → 10K
52:07
About 5:13/km or 8:23/mile.
50:00 10K → Half
1:50:19
About 5:14/km or 8:25/mile.
1:45 Half → Marathon
3:38:55
A mathematical equivalency, not proof of marathon readiness.
Why marathon predictions deserve extra caution
A large study of recreational endurance runners found standard Riegel predictions were reasonably calibrated through the half marathon but substantially underestimated marathon times. For half of the runners, the marathon prediction was at least 10 minutes too fast.
That does not make the formula useless. It means a short-race result measures only part of what determines a marathon.
- Long-run durability
- Weekly training volume
- Fueling and hydration practice
- Pacing discipline
- Heat, wind and course profile
- Whether the recent race and marathon are from the same fitness cycle
What to do with your predicted race time
- Look at the formula spread: if the models are close, the mathematical assumptions are producing a similar answer. If they are far apart, do not hide that uncertainty.
- Check the pace: ask whether the implied pace fits recent training rather than choosing the fastest formula.
- Use a tune-up race: a closer-distance result later in the training cycle is usually more informative than an old short race.
- For marathon: let long runs, fueling practice and marathon-specific training overrule an aggressive short-race equivalency.
Turn the prediction into a race plan
Use the Split Calculator for exact checkpoints or build a training schedule around the goal.
Open the Running Split CalculatorRace time calculator FAQ
What is the Riegel race prediction formula?
Why might a marathon prediction be too fast?
Is Cameron better than Riegel?
Why add a second recent race?
Can I predict a marathon from a 5K?
Can I use a training run instead of a race?
Bottom line
Start with Riegel 1.06, prefer recent results near your target distance, and use the prediction as a planning baseline. The farther the target is from the race you entered, the more your actual training matters.
Research reviewed: Riegel, Athletic Records and Human Endurance (1981); Vickers & Vertosick, recreational endurance race-time study (2016); Blythe & Király, individual running-performance prediction (2016). Cameron is retained as a commonly used empirical comparison; its original derivation is not presented here as a peer-reviewed validation study.