Running Pace Calculator
Convert between running pace (min/mi, min/km) and speed (mph, km/h). Calculate finish times for any distance from your pace or speed.
Race Time Predictor Calculator
Predict your finish times for 5K, 10K, half marathon, marathon, and custom distances using the Riegel and Cameron formulas from a known race result.
h
min
sec
Known Result: 10K
50:00
Pace: 8:03 /mile
Predicted Finish Times
1 Mile
32:27
32:27 /mi
5K
38:02
12:14 /mi
15K
1:02:52
6:45 /mi
Half Marathon
1:19:05
6:02 /mi
Marathon
2:17:31
5:15 /mi
50K (Ultra)
2:39:43
5:08 /mi
Formula Comparison
| Distance | Riegel | Cameron | Average | Pace /mile | Pace /km |
|---|---|---|---|---|---|
| 10K ★ | 50:00 | 50:00 | 8:03 | 5:00 | |
| 1 Mile | 7:13 | 57:42 | 32:27 | 32:27 | 20:10 |
| 5K | 23:59 | 52:05 | 38:02 | 12:14 | 7:36 |
| 15K | 1:16:51 | 48:53 | 1:02:52 | 6:45 | 4:11 |
| Half Marathon | 1:50:19 | 47:51 | 1:19:05 | 6:02 | 3:45 |
| Marathon | 3:50:01 | 45:02 | 2:17:31 | 5:15 | 3:16 |
| 50K (Ultra) | 4:35:21 | 44:05 | 2:39:43 | 5:08 | 3:12 |
Pace Decay Curve
32:27
1 Mile
12:14
5K
8:03
10K
6:45
15K
6:02
HalfM
5:15
Marathon
5:08
50K (Ultra)
Note: Predictions assume adequate training for the target distance and similar race conditions. Results are less reliable when predicting more than 4× your known distance. Add 5–10% for conservative marathon goals from 5K times.
Planning notes, formulas, and examples
About the Race Time Predictor Calculator
Race-equivalency formulas estimate how a recent result might translate to other distances.
This calculator applies the Riegel formula and the Cameron model to show equivalent performances from one race distance to another. The estimates work best when the source performance is recent and your training supports the target distance.
Use the results as goal ranges and planning references rather than as guarantees of race-day outcome.
When This Page Helps
It is useful for setting goal ranges, checking training paces, and comparing performances across distances. Predictions become less reliable as you move farther from the event you raced, especially when stepping up to half-marathon or marathon distances without specific preparation.
How to Use the Inputs
- Select the distance of a recent race you've completed.
- Enter your finish time for that race.
- View predicted finish times across all standard distances.
- Compare Riegel vs Cameron predictions for a range estimate.
- Use predictions to set goal times for your next race.
Formula used
Riegel Formula (1977):
T2 = T1 × (D2 / D1)^1.06
Where:
• T1 = known race time
• D1 = known race distance
• D2 = target race distance
• 1.06 = fatigue exponent
Cameron Formula:
T2 = T1 × (D2 / D1) × adjusted decay factor
The fatigue exponent varies by fitness level (1.06 for most runners, 1.01–1.04 for elites).Example Calculation
Result: 5K: 24:09 | Half Marathon: 1:50:15 | Marathon: 3:50:56
From a 50:00 10K: Riegel predicts the 5K at 24:09 (T = 50 × (5/10)^1.06 = 24.15 min). The half marathon prediction is 1:50:15, and the full marathon is 3:50:56. These assume fitness is specific to the known distance — if you've only trained for 10K, the marathon prediction may be optimistic.
Tips & Best Practices
- Use a recent race (within 4–6 weeks) for the most accurate predictions.
- Predictions are most accurate when the target distance is within 2–4× of the known distance.
- A 5K time is less reliable for predicting marathon performance than a 10K or half marathon time.
- Elite and highly trained runners may use a lower fatigue exponent (1.01–1.04) instead of the standard 1.06.
- If your race was on a hilly, hot, or windy course, your flat-course equivalent may be faster.
- These formulas assume adequate training for the target distance — speed alone won't carry you through a marathon without the mileage base.
The Mathematics of Fatigue
Peter Riegel published his formula in 1977, demonstrating that race performance follows a power-law relationship with distance. The exponent of 1.06 was derived from analysis of world records across distances from 100 meters to 100 miles. Remarkably, this simple formula explains over 99% of the variance in world record times.
When Predictions Fail
The biggest prediction failures occur when: (1) the runner hasn't trained specifically for the target distance, (2) race conditions differ dramatically (flat 5K vs hilly marathon), (3) the runner has a significant speed/endurance imbalance. A sprinter-type runner will outperform predictions at 5K but underperform at the marathon.
Using Predictions for Training
Race predictions aren't just for setting goals — they help calibrate training paces. If your predicted marathon is 4:00:00, you know your goal marathon pace is 9:09/mile. From this, you can derive your easy pace (10:30–11:30), tempo pace (8:20–8:40), and interval pace (7:15–7:45) using established coaching tables.
Sources & Methodology
Last updated:
Methodology
This calculator projects equivalent race times from a known result using two common distance-decay approaches, then presents them as a planning range. The output is most useful when the input race is recent and the target event is supported by similar training. The Cameron result is shown as a comparison model, while the Riegel formula is the primary reference point.
Sources
- Riegel race prediction equation (Peter Riegel / Runner's World) — Historical source for the power-law race prediction equation used as the primary model.
- Daniels' Running Formula (Human Kinetics) — Used for race-equivalency and training-pace context around prediction outputs.
Frequently Asked Questions
The Riegel formula is accurate to within 1–3% for well-trained runners predicting between similar distances (e.g., 10K to half marathon). Accuracy decreases when predicting much longer distances from short races (e.g., 5K to marathon), as it doesn't account for fueling, hydration, and long-distance specific training.
Predictions from 5K to marathon are the least reliable because they span a 8.4× distance multiplier. Your 5K fitness reflects neuromuscular speed and VO₂max, while marathon performance depends heavily on fat oxidation, glycogen storage, and long-run durability. Adjust the prediction by adding 5–10% for a more realistic marathon estimate.
The exponent (1.06 in Riegel's formula) represents how much pace slows as distance increases. A value of 1.0 would mean no slowdown (same pace at all distances). Higher values mean more fatigue effect. Elite runners have lower exponents (1.01–1.04) because their endurance training minimizes pace decay.
Both are well-validated. Riegel's formula is simpler and widely used since 1977. The Cameron model uses a slightly different mathematical approach that some studies find marginally more accurate for marathon predictions specifically. Using both gives you a range, which is more useful than a single point estimate.
They work best for runners who are well-trained at their known distance. Beginners often have disproportionate speed at short distances (e.g., fast 5K) but lack the endurance base for equivalent long-distance performance. If you're new to running, add 5–15% to the marathon prediction for a more conservative goal.
Use your most recent race time (within 4–6 weeks) that reflects your current fitness, not necessarily your all-time PR. A PR from two years ago may not represent your current capabilities. The prediction is only as good as the input data.
More in this topic
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