Calculator
Example Data Table
| Session | Distance | Time | Pace (km) | Pace (mile) | Predicted 10K |
|---|---|---|---|---|---|
| Long run | 16.0 km | 01:24:00 | 5:15 | 8:27 | 00:52:35 |
| Steady endurance | 10.0 km | 00:50:00 | 5:00 | 8:03 | 00:50:00 |
| Tempo combo | 8.0 km | 00:38:24 | 4:48 | 7:43 | 00:48:39 |
Formula Used
- Pace: pace = total_time_seconds ÷ distance (per km or per mile).
- Speed: km/h = distance_km ÷ (time_seconds ÷ 3600).
- Unit conversion: miles = kilometers ÷ 1.609344.
- Riegel prediction: T₂ = T₁ × (D₂ ÷ D₁)exponent.
How to Use This Calculator
- Enter your completed distance and choose the unit.
- Enter your workout time in hours, minutes, and seconds.
- Keep exponent at 1.06, or tune it to match your races.
- Enable splits to view cumulative checkpoints and chart.
- Press Calculate to show results above the form.
- Download CSV or PDF to log the session in your tracker.
Endurance pacing in weekly volume planning
For many runners, endurance work makes up 65–85% of weekly running time. A controlled endurance pace typically sits 15–30% slower than recent 10K pace. Using this calculator, log one steady session and keep the pace consistent across similar runs to stabilize training load.
Distance and time normalization for mixed routes
Comparing treadmill kilometers to outdoor miles is easier when every session is converted to both units. The tool converts miles using 1.609344 km per mile and reports pace in min/km and min/mi. This allows quick audits of pacing drift across different environments.
Split checkpoints for negative-split practice
Enable cumulative splits to create checkpoints every 1 km, 2 km, or 1 mile. If the plot line bends upward late, it indicates slowing. A flat, near-linear curve signals stable effort. For long runs, aim for a final 20% that is 5–10 seconds per km faster than the first 20%.
Speed metrics for cross-training translation
Some athletes prefer speed targets for bikes or ellipticals. The calculator outputs km/h and mph so you can match aerobic intensity across modalities. For example, moving from 10.5 km/h to 11.0 km/h is a 4.8% increase, which is significant if repeated weekly.
Finish-time projections for realistic goal setting
The Riegel model estimates time at new distances using T₂ = T₁ × (D₂ ÷ D₁)^exponent. A common exponent is 1.06, while less endurance may fit 1.08–1.10. Use your best recent effort, not a fatigued long run, to avoid optimistic forecasts.
Exporting results for coaching and review
CSV exports work well for monthly trend tables: pace, speed, and predicted outcomes in one file. The PDF snapshot is useful for sharing with a coach or training group. Keep notes on terrain, temperature, and fatigue to interpret pace changes with context.
FAQs
What is a good endurance pace?
It is usually conversational and sustainable. Many athletes run it about 15–30% slower than recent 10K pace, adjusted for hills, heat, and fatigue.
Why does the calculator ask for an exponent?
The exponent shapes how time scales with distance in the Riegel model. Higher values predict bigger slowdowns over longer events, which often matches newer runners.
Should I use race time or training time as input?
Use a best recent effort with steady pacing, ideally a race or time trial. Easy-run times can understate fitness and lead to conservative predictions.
How accurate are the predicted finish times?
They are estimates, not guarantees. Accuracy improves when your input effort is maximal and recent, and when the chosen exponent matches your endurance history.
Why do my pace and speed look inconsistent?
Small rounding differences are normal. Also, pace is time per distance while speed is distance per time. Check unit selection and ensure time fields are correct.
Can I use this for walking or hiking?
Yes. Enter distance and time the same way. Predictions may be less meaningful if terrain changes a lot, but pace, speed, and exports remain useful.