Sportsrunningraceprediction

Race Time Predictor

The race time predictor applies the Riegel endurance formula to extrapolate your expected finish time at a new distance from a recent race result. It accounts for the fact that performance degrades slightly faster than linearly as distance increases, making it more accurate than simple proportional scaling.

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Formula

Predicted Time = Known Time × (Target Distance / Known Distance)^1.06

The Riegel formula raises the distance ratio to the power of 1.06 rather than 1.0, capturing the empirical observation that runners slow down slightly as race distance increases. The exponent was derived from analysis of world record performances across distances and has proven accurate for most recreational runners when the known and target distances are within a factor of about four of each other.

How to use the Race Time Predictor

  1. 1

    Enter your known race distance

    Value should be in miles.

  2. 2

    Enter your known race time

    Value should be in minutes.

  3. 3

    Enter your target race distance

    Value should be in miles.

  4. 4

    Read your results instantly

    Results update in real time as you type.

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How the Riegel formula works

Physiologist Peter Riegel published his race time prediction formula in 1977 after studying world record performances across a wide range of distances. He found that the relationship between time and distance follows a power law with an exponent of approximately 1.06. This means that doubling the distance takes slightly more than twice as long — about 2^1.06 = 2.08 times as long. In practical terms, if you run a 5K in 25 minutes, the formula predicts a 10K around 51:30 rather than exactly 50:00. The extra 90 seconds reflects the reality of accumulating fatigue. The formula works best for predictions within a similar endurance range — using a sprint time to predict a marathon will overestimate performance significantly.

Limitations and adjustments

The Riegel formula assumes similar race conditions and consistent training. Several factors can cause actual performance to deviate from the prediction: course elevation, temperature, race-day nutrition, and whether you tapered adequately. For ultramarathon distances, the exponent increases substantially — some researchers use 1.15 or higher for distances beyond 50 miles. Runners who do a high volume of long runs may outperform the prediction at the marathon, while those who primarily train for shorter distances may underperform. Use the prediction as a starting point, then adjust based on your recent long-run workouts and overall training volume.

Tips & Insights

Use a recent race, not a training run

Predictions are most accurate when the known time comes from a recent, fully-tapered race effort — not a training run where you held back.

Avoid huge distance jumps

The formula is most reliable when the target distance is within two to three times the known distance. Predicting a marathon from a mile time will be far less accurate.

Cross-check with multiple distances

If you have recent times at several distances, run the prediction from each and average the results to get a more robust estimate.

Worked Examples

Predict marathon from 10K

known_distance_miles: 6.2known_time_minutes: 52target_distance_miles: 26.22

Predicted marathon: ~236 minutes (3:56)

Predict half marathon from 5K

known_distance_miles: 3.1known_time_minutes: 24target_distance_miles: 13.1

Predicted half marathon: ~109 minutes (1:49)

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Frequently Asked Questions

How accurate is the Riegel formula?

For most recreational runners predicting across similar distances (e.g., 5K to half marathon), accuracy is typically within 3–5%. Accuracy decreases for very long distances or when using a time from a very different distance.

Can I use a training run time instead of a race time?

You can, but results will be less accurate. Training runs are typically run at sub-maximal effort, so they will underestimate your race capability. Use a time-trial effort for best results.

Why does the exponent matter?

An exponent of exactly 1.0 would mean performance scales linearly with distance — doubling the distance exactly doubles the time. The exponent of 1.06 accounts for the physiological cost of sustaining effort over longer durations.

Is this formula used by coaches?

Yes, many coaches use Riegel's formula or similar equivalency tables to set pace targets for workouts and races. It is also embedded in many GPS watch training plan features.

What if my predicted time seems way off?

Large discrepancies usually mean the distances being compared are too different, your known result was not a maximal effort, or you have a particular strength or weakness at certain distances due to your training background.

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