MariposasRace Time Predictor
By Zachary, builder of Mariposas · Reviewed against published exercise-science sources (references)
· Last updated June 2026
Cardio & Running Riegel estimates; big jumps (5K→marathon) read optimistic.
Plug in a recent race result and target distance to predict your finish time using Riegel’s formula. Best for nearby distances; very large jumps (5K to marathon) tend to read optimistic.
How it works
Riegel's formula, published by Peter Riegel in a 1977 Runner's World article and later refined, expresses the relationship between race distance and finish time as T2 = T1 × (D2 / D1) ^ 1.06. That exponent of 1.06 is the core of the thing: it captures the well-documented reality that pace slows as distance increases, because aerobic demand, glycogen depletion, and cumulative muscular fatigue compound over longer efforts. A perfectly linear model would assume your 10K pace scales exactly to your half marathon pace, which no runner experiences. The 1.06 exponent bends that curve slightly upward, adding time as the distance gap widens. Because the exponent was derived from road race performance data across a broad population, it reflects average fatigue rates rather than any individual runner's physiology, which is why the formula gets less reliable the further the two distances sit apart.
When to use it
This calculator is most useful for runners setting a realistic goal pace before registering for a new distance, or for coaches building training paces from a recent race benchmark. It also helps spot whether a runner is undertrained or overtrained relative to their recent results: if your predicted marathon time feels far off from what you actually ran, that gap often points to a pacing error, nutrition failure, or a base that needs more mileage at the longer distance.
Worked example
Say you ran a recent 10K in 48:30 and you want to predict your half marathon finish. Plugging D1 = 10K, T1 = 48:30, and D2 = 21.1K into Riegel's formula gives a predicted half marathon time of roughly 1:45:50. That translates to an average pace of about 5:01 per kilometer, compared to your 10K pace of 4:51 per kilometer. The formula is telling you to expect roughly 10 seconds per kilometer of slowdown over that distance jump, which is a useful anchor for deciding whether to target a sub-1:45 or treat your first half as a controlled effort near 1:46.
Tips for an accurate result
- Use a race result, not a training run. Time trials and solo efforts rarely reflect the same conditions as a competitive race with pacing support, a crowd, and a measured course, so they tend to inflate predicted results.
- The closer the two distances, the more accurate the output. A 5K to 10K prediction is far more reliable than a 5K to marathon prediction, where the formula routinely underpredicts finish time by 10 to 20 minutes for average runners.
- Account for course profile separately. Riegel's formula assumes flat road conditions. If your reference race was flat but your target race has significant elevation, add time manually rather than expecting the formula to handle it.
- Make sure your reference race is recent and reflects current fitness. A PR from two years ago produces a prediction for who you were then, not who you are now.
- If you have two recent race results at different distances, run the prediction both ways and see if the outputs agree. A large discrepancy suggests one race was an outlier, whether from weather, illness, or a bad day, and averaging the two predictions often gives a more grounded target.
Formula & sources: methodology · references.
Now go hit the number Mariposas turns every workout, run and class into progress · collect a cute pet 🐾FAQ
- Why does the formula tend to be optimistic for the marathon?
- The 1.06 exponent was fit to a broad dataset, but marathon performance is disproportionately affected by glycogen depletion around miles 18 to 22. Most runners slow far more sharply in the final third than the formula anticipates. Many coaches apply a corrected exponent closer to 1.07 or 1.08 for marathon predictions specifically, which adds several minutes to the output and tends to align better with real results.
- Can I use a training run instead of a race as my input?
- You can, but the prediction will likely be optimistic. Solo runs without competitive pressure, often done on familiar flat routes, tend to be a few percent faster than what a runner holds in an actual race across a new course. A time trial done with genuine all-out effort on a measured course is the next-best substitute if a recent race is not available.
- How accurate is Riegel's formula in practice?
- For adjacent distances like 5K to 10K or 10K to half marathon, many runners find the prediction lands within 2 to 4 percent of their actual time when fitness is current and the race goes smoothly. Over larger jumps the error grows, and individual factors like heat tolerance, aerobic base depth, and fueling strategy start to matter more than any formula can capture.
- Does the formula work for cycling or swimming?
- Riegel's original work focused on running, but the same formula structure has been applied to other endurance sports with mixed results. The exponent may differ for cycling because rolling resistance and drafting dynamics change the fatigue curve differently than foot-strike accumulation does in running. Treat non-running predictions as rougher approximations.
- What if my predicted time is faster than my actual marathon PR?
- That almost always means the reference race is from a shorter distance where the formula's optimism is most pronounced. The practical fix is to use a longer reference race closer to the marathon distance, like a half marathon, which gives the exponent less room to compound the error. A predicted time that feels unreachable is often the formula's way of signaling that long-run volume or race-specific endurance needs more development.