Race Time Predictor
Predict your finishing time at a new race distance from a known time at another, using Riegel's endurance formula, with the equivalent pace.
Como usar esta calculadora
- 1Enter a distance you've raced and your time for it, in minutes.
- 2Choose the units for that distance.
- 3Enter the target distance you want a prediction for.
- 4Read your predicted finishing time and equivalent pace.
Como funciona
Riegel's race prediction
T₂ = T₁ × (D₂ ÷ D₁)^1.06 T = time, D = distance the exponent 1.06 > 1 makes longer races slower per unit distance most accurate between nearby distances
Riegel's formula predicts a race time at one distance from a known time at another, based on the empirical observation of how running performance scales with distance. If pace stayed perfectly constant, the time would simply scale in direct proportion to distance, an exponent of exactly 1. But runners slow down as races get longer — nobody holds their sprint pace for a marathon — so the formula raises the distance ratio to the power 1.06, slightly more than 1, which stretches the predicted time upward for longer distances and compresses it for shorter ones. This fatigue exponent, derived by Pete Riegel from analysing race results, captures the typical fall-off in pace across the middle-distance to marathon range remarkably well. The prediction is most reliable when the known and target distances are not too far apart and when the runner is trained for the endurance the target distance requires.
Exemplo resolvido
A runner who covers 5 km in 25 minutes is predicted, by Riegel's formula, to run 10 km in 25 × (10 ÷ 5)^1.06 ≈ 25 × 2.085 ≈ 52 minutes — a little more than double the 5K time, reflecting the slight slowing over the longer distance rather than a perfect doubling.
Race Time Predictor: o guia completo
Why longer races are slower per mile
Anyone who has run different distances knows that pace and distance trade off: you can sprint a short race far faster, per mile, than you can sustain over a long one. A world-class 100-metre pace would be unthinkable over a mile, and a mile pace impossible to hold for a marathon. This is the fundamental fact Riegel's formula encodes. If a runner could hold the same pace regardless of distance, predicting times would be trivial multiplication — but the reality of human endurance is that the body cannot sustain its shorter-distance intensity as the distance grows.
The formula captures this with a single number: the exponent 1.06. An exponent of exactly 1 would mean perfectly proportional times and constant pace. By making it slightly larger, Riegel builds in the gentle, predictable slowing that real runners experience. The 6% above 1 is small but compounds over large distance ratios, which is why a marathon takes noticeably more than eight times a 5K time even though it is only about eight times the distance. This exponent was not guessed but fitted to large amounts of real race data, which is why the formula works as well as it does across the common racing distances.
How accurate is the prediction?
Riegel's formula is a genuinely useful predictor, but it is a model, and knowing its limits keeps expectations realistic. It is most accurate when the known and target distances are reasonably close — predicting a 10K from a 5K, or a half-marathon from a 10K, tends to be reliable. The further apart the distances, the more the prediction depends on the assumption that the runner's endurance scales in the standard way, and individual variation grows. Predicting a full marathon from a single 5K time is the classic stretch, and it usually comes out optimistic.
The reason is that the formula assumes the runner is equally well trained for both distances, which is often not true. Marathon performance depends heavily on specific endurance built through long runs and high mileage, and a runner with fast 5K speed but little long-distance training will fall short of the marathon time the formula predicts. Conversely, a well-trained marathoner might beat their 5K-based prediction over the longer race. Terrain, weather, pacing discipline, and fuelling all matter too. The prediction is best treated as a reasonable target under good conditions and proper training, not a guarantee — a benchmark to aim for rather than a certainty.
Using predictions to train and pace
Beyond satisfying curiosity, race prediction has real practical value in training and racing. The most important use is setting a realistic goal pace. Runners who go out too fast in the early miles of a longer race, misjudging what their fitness can sustain, famously 'hit the wall' and slow dramatically at the end. A prediction grounded in a recent shorter-race result gives an honest target pace, helping a runner start at a sustainable effort rather than an aspirational one that leads to collapse late on.
Predictions also help structure training and measure progress. Comparing a race result to what the formula predicts from another distance reveals whether a runner's strength lies in speed or endurance — beating the prediction over longer distances suggests strong endurance, falling short suggests a need for more long-distance work. Tracking how predicted times improve over a training block gives a sense of fitness gains across distances, not just the one you happened to race. Coaches and training plans use these relationships to prescribe paces for different workouts. The formula turns a single race result into a whole map of expected performances, which is far more useful for planning than one isolated time.
Perguntas frequentes
How does a race time predictor work?
It uses Riegel's formula: T₂ = T₁ × (D₂ ÷ D₁)^1.06. Your time and distance for one race predict the time at another, with the 1.06 exponent accounting for the slowing that happens over longer distances. A 25-minute 5K predicts about 52 minutes for 10K.
How accurate are race predictions?
Quite accurate between nearby distances (5K to 10K, 10K to half-marathon) for a well-trained runner. They get less reliable over big jumps — predicting a marathon from a 5K is usually optimistic, because the marathon needs specific long-distance training the formula assumes you have.
Why do longer races have slower paces?
Because the body can't sustain shorter-distance intensity over longer distances — endurance limits force you to slow down. Riegel's formula captures this with an exponent slightly above 1 (1.06), which stretches predicted times upward for longer races rather than assuming constant pace.
Can I use this to set a goal pace?
Yes — that's one of its best uses. A prediction from a recent shorter race gives a realistic target pace, helping you avoid starting too fast and fading late. Treat it as an achievable target under good conditions and proper training, not a guarantee, and adjust for hills, heat, and your endurance base.