The Cameron Formula
An alternative race time predictor built on how average speed falls with distance.
The Cameron formula, developed by Dave Cameron, predicts race times from a curve of how a runner's average speed falls as the distance grows. Unlike Riegel's fixed-exponent formula , Cameron's curve is steep over short distances and flattens over long ones, so how much a prediction slows down depends on where the two races sit on it.
THE FORMULA
T2 = T1 × (D2/D1) × [f(D1) / f(D2)]
f(d) = a − b·d + c / dk
How the formula works
Cameron's function f(d) = a − b·d + c / dk, with d in metres, stands for the average speed a runner can hold over a distance. It falls quickly over the first few kilometres and slowly after that. A prediction is the known time scaled by the distance and by the ratio of the two speeds: T2 = T1 × (D2/D1) × f(D1)/f(D2).
From a 5K or a 10K to the marathon, f(D1)/f(D2) is about 1.16 and 1.11, so Cameron slows the pace down more than Riegel's fixed exponent does: the marathon it predicts is a few minutes slower. Between neighbouring distances (5K → 10K, 10K → half marathon) the two formulas agree within seconds.
Calcpace uses the metric version Cameron published in 2001, fitted to performances from 800 m to the marathon. Far beyond that the curve stops making sense (it reaches zero near 445 km), so Calcpace only uses Cameron up to 100 km; for longer distances, use Riegel.
Example
You ran a 10K in 42:00. What's your predicted marathon?
f(10000) ≈ 13.7687
f(42195) ≈ 12.4001
T2 = 2520 × (42195/10000) × (13.7687 / 12.4001)
T2 ≈ 11,807 s ≈ 3:16:46
Riegel gives 3:13:12 for the same input: Cameron is a few minutes more cautious.
Cameron vs Riegel — when to use each
| Known → Target | Cameron | Riegel | Difference |
|---|---|---|---|
| 5K (20:00) → 10K | 41:39 | 41:41 | −0:02 (practically the same) |
| 5K (20:00) → Marathon | 3:15:11 | 3:11:49 | +3:22 (Cameron more conservative) |
| 10K (42:00) → Marathon | 3:16:46 | 3:13:12 | +3:34 (Cameron more conservative) |
Neither formula accounts for terrain, training history, or race-day conditions. Use them as reference points, not guarantees.
Try both formulas side by side
Enter a known race result and compare Riegel vs Cameron predictions.
Cameron Formula: When and How to Use It
The Cameron formula, developed by Dave Cameron, predicts race times from a curve of how average speed falls with distance — steep over short races, flatter over long ones. Unlike Riegel's single fixed exponent, the slowdown it predicts depends on where the two distances sit on that curve. Calcpace uses the metric version Cameron published in 2001, with distances in metres.
In practice, Cameron is more conservative than Riegel whenever the target is a marathon: a few minutes slower from a 5K, a 10K or a half marathon. For predictions between adjacent distances, both formulas agree closely. The predictor on Calcpace runs both in parallel so you can compare.
Neither formula is universally more accurate — both are empirical models with known limitations. The most useful approach is to treat the range between the two outputs as a confidence interval for your goal time. If Riegel says 3:10 and Cameron says 3:18, a realistic target sits somewhere in that corridor, assuming your training matches the goal distance.
How does this work?
When should I use Cameron instead of Riegel?
Use Cameron as a cautious second opinion when predicting a long race — a marathon above all — from a short one, such as a 5K or a 10K: it slows the pace down more than Riegel does, leaving room for the endurance a short race does not test. For adjacent-distance predictions (10K to half marathon), the two formulas give very similar results.
Which formula is more accurate?
Neither is universally superior. Both were derived from large race databases and capture different aspects of the distance-speed relationship. Real-world accuracy depends on effort quality, course profile, weather, and training specificity — none of which either formula models. Run both and use the range.
Can I use these predictions for ultra-marathons?
No — both formulas were calibrated on race data up to the marathon, and Calcpace only runs Cameron up to 100 km. At ultra distances (50K, 100K, 100 miles), performance is dominated by fueling, sleep, terrain, and mental resilience that no pace-based formula captures. Course-specific databases and coach guidance are far more reliable for ultras.