Kalkulátorok
Jó általános választás. Akkor működik a legjobban, ha a távolságok hasonlóak. — pl. 10K → félmaraton
Jobb, ha a távolságok nagyon eltérnek. Korrigálja a sebességet rövid versenyeknél. — pl. 1 mérföld → maraton
How Race Prediction Formulas Work
Predicting race performance is both a science and an art. Our Race Predictor uses two of the most respected mathematical models in sports physiology—Riegel and Cameron—to estimate your potential finish times based on a recent result.
The Riegel Formula (T2 = T1 × (D2/D1)^1.06) assumes that your aerobic capacity remains relatively consistent as you move up in distance. It is the gold standard for predicting distances between 5K and the Marathon.
The Cameron Formula introduces a distance-correction factor. Dave Cameron analyzed thousands of race results and found that some runners 'fade' more than others as distances increase. This model is often more accurate for runners who are moving from very short distances (like 1 mile) to the Marathon.
Both formulas assume you ran close to your maximum effort on a flat road course under normal conditions. They do not account for heat, altitude, or cumulative fatigue from heavy training. Use the predictions as realistic targets, then adjust for the specific conditions of your upcoming race.
Hogyan működik?
Why is my predicted marathon time so much faster than my actual PB?
Formulas assume you have done the specific training required for the target distance. A 20-minute 5K predicts a sub-3:10 marathon, but only if you have built the necessary endurance base and high-mileage volume.
Should I use Riegel or Cameron for my prediction?
Use Riegel when predicting between distances of similar aerobic demand (10K → half marathon, half → marathon). Use Cameron when predicting from short distances (5K or 1 mile) to much longer ones, as Cameron accounts for the larger role of speed over endurance in short events.
How accurate are race prediction formulas?
For well-trained runners predicting between adjacent distances (10K → half, half → marathon), accuracy is typically within 2–5%. Accuracy drops as the gap between known and target distance grows. Environmental factors like heat, hills, and fatigue are not modelled — always treat the prediction as a starting point, not a guarantee.