Free Running Pace Calculator & Predictor

Runner's Pace Predictor

Predict race finish times using the Riegel formula — free, instant.

Distance (km)

Time (mm:ss)

Predicting a Race Time You Haven't Run Yet

Runners training for a distance they haven't raced before often want a realistic target time before race day — this tool takes a known recent result at one distance and predicts an equivalent-effort finish time at a different distance, using the Riegel formula, a well-established method in exercise science for this exact kind of cross-distance prediction.

How the Riegel Formula Actually Works

Developed by researcher Pete Riegel, the formula predicts a new race time based on a known time at a different distance, using the relationship T2 = T1 × (D2/D1)^1.06 — where the 1.06 exponent reflects the well-documented reality that pace naturally slows somewhat as race distance increases, rather than staying perfectly linear. This exponent was derived from analyzing large sets of real race performance data across distances, which is why it's become a widely referenced standard for this kind of prediction rather than an arbitrary guess.

A Worked Example

A runner who recently completed a 10K in 50 minutes wants to predict their marathon time. Applying the Riegel formula to that 10K result predicts a marathon finish time in the roughly 3 hour 55 minute range — noticeably slower per-kilometer pace than their 10K pace, which correctly reflects that maintaining 10K-level intensity for a full marathon simply isn't physiologically realistic, even for a well-trained runner, and the formula's exponent specifically accounts for that expected slowdown.

Where This Prediction Actually Helps

A runner setting a realistic goal pace for an upcoming race at a new distance, rather than guessing based on a rough feeling. Coaches using a recent time trial result to estimate an athlete's readiness for an upcoming race distance. Someone deciding between two race distance options, using predicted times to understand roughly what each would realistically demand. Anyone building a training plan who wants a data-grounded target pace to structure workouts around.

Where the Prediction Gets Less Reliable

The formula assumes reasonably consistent training and conditioning across both distances — it's most accurate when the known result and predicted distance aren't wildly different in nature (a 5K to 10K prediction is more reliable than a 5K to marathon prediction, since ultra-endurance events introduce factors like fueling strategy and pacing discipline that a shorter race doesn't test at all). It also can't account for race-day variables like weather, course terrain, or how well-trained you specifically are for the longer distance's unique demands, like a marathon's fueling and pacing strategy.

Using the Prediction as a Starting Point, Not a Guarantee

A Riegel prediction gives a physiologically grounded target, not a promised outcome — treat it as a realistic goal-setting anchor for training purposes, adjusted based on how training for the new distance actually progresses, rather than an exact number to hold yourself to regardless of how race day actually unfolds.

Calculated Instantly, On Your Device

The formula's calculation runs with client-side JavaScript the moment you enter your known time and target distance — a straightforward mathematical operation that doesn't require any server processing.

A Second Example

A runner with a recent half-marathon time of 1 hour 45 minutes considering their first full marathon uses the predicted Riegel time as a starting goal pace for structuring their marathon training plan's long-run pacing, while planning to reassess that target based on how training actually progresses over the following months.

How accurate is the Riegel formula in practice?

It's a well-regarded general estimation method, reasonably accurate for most runners across moderate distance changes, though individual results vary based on training, race-day conditions, and how well-suited a runner is to the specific new distance.

Why does my predicted marathon pace seem so much slower than my 5K pace?

This reflects the formula's built-in adjustment for the well-documented reality that sustainable pace naturally decreases as race distance increases — it's expected, not an error in the calculation.

Can I use this to predict a shorter distance from a longer one, like a 5K from a marathon time?

Yes — the formula works in both directions, predicting either a longer or shorter distance's equivalent-effort time from a known result at a different distance.

Should I set my race goal exactly at the predicted time?

Treat it as a reasonable planning anchor rather than a fixed target — actual race-day performance depends on training progress, conditions, and pacing strategy specific to the new distance.

Does this formula account for hills or a difficult race course?

No — it's based purely on distance and a known time, not course-specific factors like elevation gain, which racers should factor in separately when setting a final goal pace.

Riegel vs. Other Prediction Methods

Other race-time prediction approaches exist — VO2 max-based calculators, or simpler linear pace extrapolation — but Riegel's formula remains one of the most widely referenced specifically because its exponent was derived from analyzing large volumes of actual race result data across distances, rather than a purely theoretical physiological model, which is part of why it's held up reasonably well as a practical estimation tool across several decades of use by coaches and runners.