Calculator

Race time predictor.

Enter your recent race result and we’ll predict finish times for other distances using the Riegel model. Switch between metric and imperial, and see a full table of predictions.

Predict times from a recent result

Recent distance (km)

Recent finish time (H / M / S)

Enter hours, minutes, seconds separately (e.g., 0 • 50 • 0 for 50 minutes).

Target distance (km)

Predicted times table

Distance	Predicted Time
1 km	—
1 mile	—
5 km	—
10 km	—
Half marathon	—
Marathon	—

How the prediction works

This tool uses the Riegel model, which estimates how performance scales with distance: T₂ = T₁ × (D₂/D₁)^1.06. The exponent (≈1.06) reflects increasing fatigue with longer distances. You can use any distance/time pair as your recent result; the prediction works on the ratio, so units (km vs miles) cancel out.

Worked examples

Examples rounded to the nearest second.
Recent	Target	Prediction
10K in 50:00	Half marathon	≈ 1:50:25
5K in 24:00	10K	≈ 49:47
Half marathon in 1:45:00	Marathon	≈ 3:39:40

Caveats & context

Predictions assume similar conditions (course, weather, fueling, fitness) and even pacing.
Exponents vary by athlete & distance (≈1.03–1.10). Longer races often yield larger exponents.
Use predictions for planning; actual results may differ with fatigue and training specificity.

Related tools

Interpreting your prediction

Enter a recent result and target distance to see a personalised explanation here, including equivalent pace per km/mi and tips for adjusting for course profile and weather.

Frequently asked questions

What exponent should I use?

1.06 is a common default. Shorter events or highly trained athletes may see ≈1.03–1.05, while longer events might be ≈1.07–1.10.

Does terrain or heat change the prediction?

Yes. Hills, heat, wind, or technical trails reduce pace. Adjust expectations or use event‑specific data.

Can I predict ultra distances?

Extrapolation grows less reliable the further you get from your recent race. Treat ultra predictions as rough planning numbers.

Inside the race-time formula

Predictions use the Riegel power-law model: T₂ = T₁ × (D₂ ÷ D₁)^k. We convert every distance to metres (1 mile = 1609.34 m) and every time to total seconds so that the ratio works regardless of units.

How the calculation unfolds

Interpret your recent result as D₁ and T₁, converting inputs to metres and seconds.
Convert the target distance D₂ to metres, raise the distance ratio to the exponent k (default 1.06), and multiply by T₁ to get T₂.
Derive equivalent pace per km/mi by dividing the predicted time by the target distance in the respective units.

Choosing an exponent

Exponent k	Best suited for	Pluses	Minuses
1.03–1.05	Track/short-road specialists with strong speed endurance.	Produces ambitious marathon/half predictions when you hold form well beyond 10K.	Optimistic for athletes building endurance or racing in tough conditions.
1.06 (default)	General road runners moving between 5K and marathon.	Matches large-sample race datasets; easy to compare with most online tools.	May slightly understate potential in short events for speed-focused runners.
1.07–1.10	Marathon-to-ultra efforts, hot/hilly courses, or limited aerobic base.	Adds extra fade for fatigue, fuelling, and terrain so goals stay realistic.	Conservative if you execute a dialled-in marathon build on a fast course.

Alternative calculators (Cameron, Daniels VDOT, McMillan) tweak the exponent or incorporate proprietary adjustments, but they follow the same power-law pattern. Track your own race history, see whether predictions skew high or low, and adjust k accordingly.