Running Pace Calculator
Calculate your running pace in minutes per kilometre and predict your finish times for popular race distances. Enter any known time and distance to get pace, splits, and race predictions using the Riegel formula trusted by coaches worldwide.
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Enter your details
Your Running Pace
ExampleExample figures, not your own. Worked for 5 km in 25 minutes. Enter your own details and press Calculate.
Pace
5:00min/km
Speed
12.0km/h
Race Predictions (Riegel Formula)
How It Works
Your pace is calculated by dividing total time by distance: pace (min/km) = time (minutes) / distance (km). Race predictions use the Riegel formula: T2 = T1 x (D2/D1)^1.06, which accounts for the natural slow-down over longer distances. This formula is widely used in running science and provides accurate estimates for distances from 1 km to marathon.
How to use it
- 1Enter the distance you ran in kilometres
- 2Enter your finish time in hours, minutes, and seconds
- 3Click "Calculate" to see your pace in min/km
- 4View predicted finish times for 5K, 10K, half marathon, and marathon
Quick Reference
| Pace (min/km) | Speed (km/h) | 5K Time | 10K Time | Half Marathon | Marathon |
|---|---|---|---|---|---|
| 4:00 | 15.0 | 20:00 | 41:35 | 1:29:21 | 3:06:36 |
| 4:30 | 13.3 | 22:30 | 46:47 | 1:40:33 | 3:29:26 |
| 5:00 | 12.0 | 25:00 | 51:59 | 1:51:44 | 3:52:16 |
| 5:30 | 10.9 | 27:30 | 57:11 | 2:02:56 | 4:15:06 |
| 6:00 | 10.0 | 30:00 | 62:23 | 2:14:08 | 4:37:56 |
| 6:30 | 9.2 | 32:30 | 67:35 | 2:25:19 | 5:00:46 |
| 7:00 | 8.6 | 35:00 | 72:47 | 2:36:31 | 5:23:36 |
| 7:30 | 8.0 | 37:30 | 77:59 | 2:47:43 | 5:46:26 |
| 8:00 | 7.5 | 40:00 | 83:11 | 2:58:54 | 6:09:16 |
Race times estimated using the Riegel formula from the listed pace at 5K.
Running Pace & Race Prediction
- T₁
- = Known race time in seconds
- D₁
- = Known race distance in km
- T₂
- = Predicted race time for target distance
- D₂
- = Target race distance in km
- 1.06
- = Riegel fatigue exponent
The Riegel formula was published in 1981 and remains one of the most widely used race prediction models. It is most accurate when predicting distances within 2-4x of the known distance.