Race Time Predictor

What is a race time predictor?

A race time predictor estimates how fast you could run one distance based on a result you have already achieved at another distance. You give the tool a recent race — say a 10 km you ran in 50:00 — and a target distance like the marathon, and it returns a likely finish time plus the pace per kilometre you would need to hold. It is the fastest way to turn a single proven result into a realistic goal for a 5 km, 10 km, half marathon, marathon, or any custom distance.

This marathon time predictor uses the well-established Riegel formula and runs entirely in your browser, so nothing you type is uploaded or stored. Enter your numbers in the box above and press Predict.

How does the race time predictor work?

The tool applies Riegel’s formula, published by engineer Pete Riegel in 1977 and still the standard for endurance prediction:

T₂ = T₁ × (D₂ ÷ D₁)^1.06

Each term, with its unit:

• T₁ — your known finish time, in hours, minutes and seconds (for example 50:00 for a 10 km).
• D₁ — the known distance you ran for that time, in kilometres (the tool converts miles with 1 mile = 1.609344 km).
• D₂ — the new distance you want predicted, in the same units.
• T₂ — the predicted finish time the tool returns.
• 1.06 — the fatigue exponent. If running were perfectly linear this would be 1.0; the extra 0.06 captures the fact that runners slow down slightly as a race gets longer.

The logic is simple: take the ratio of the new distance to the old one, raise it to the power 1.06, then multiply your known time by that factor. Because the exponent is just above 1, doubling the distance more than doubles the time — exactly what real runners experience. The tool also divides the predicted time by the new distance to show your pace per km, the steady speed you would have to hold to hit that finish.

The 1.06 exponent is what separates Riegel from a naive “same pace” estimate. Predicting a marathon at your 10 km pace would be wildly optimistic; the exponent automatically adds the slowdown.

Examples

Every example uses T₂ = T₁ × (D₂ ÷ D₁)^1.06 exactly, so you can reproduce each number by typing the same inputs into the predictor above.

Example 1 — 10 km in 50:00 predicts a marathon

Known: 10 km in 50:00. Target: marathon, 42.195 km.

50:00 × (42.195 ÷ 10)^1.06 = 50:00 × 4.2195^1.06 ≈ 3:50:00

The predictor returns a marathon of about 3:50:00, at a pace of roughly 5:27 per km. Notice the time is far more than 4.2 times the 10 km time — the 1.06 exponent has added the marathon slowdown.

Example 2 — 5 km in 25:00 predicts a 10 km

Known: 5 km in 25:00. Target: 10 km.

25:00 × (10 ÷ 5)^1.06 = 25:00 × 2^1.06 ≈ 52:00

The result is about 52 minutes (close to 52:07), a pace near 5:13 per km. Doubling the distance does not simply double the 25:00 time to 50:00; the small extra factor of 2^0.06 pushes it out by roughly two minutes.

Example 3 — half marathon in 1:45:00 predicts a marathon

Known: half marathon, 21.0975 km, in 1:45:00. Target: marathon, 42.195 km.

1:45:00 × (42.195 ÷ 21.0975)^1.06 = 1:45:00 × 2^1.06 ≈ 3:38:55

The predictor estimates about 3:38:55 for the marathon, a pace near 5:11 per km. Because a half is much closer to the marathon than a 10 km is, this prediction is usually the most trustworthy of the three.

Example 4 — 10 km in 45:00 predicts a half marathon

Known: 10 km in 45:00. Target: half marathon, 21.0975 km.

45:00 × (21.0975 ÷ 10)^1.06 ≈ 1:39:17

That works out to about 1:39:17, or roughly 4:42 per km for the half.

Riegel prediction reference table

This table starts from one known result — a 10 km in 50:00 — and works the formula out to every common distance, so you can see how the predicted time and pace grow with distance. Run the tool with your own result and the live numbers will update the same way.

Target distance	Distance (km)	Calculation	Predicted time	Pace per km
5 km	5	50:00 × (5 ÷ 10)^1.06	23:59	4:48
10 km	10	50:00 × (10 ÷ 10)^1.06	50:00	5:00
Half marathon	21.0975	50:00 × (21.0975 ÷ 10)^1.06	1:50:19	5:14
Marathon	42.195	50:00 × (42.195 ÷ 10)^1.06	3:50:01	5:27

The pace per km rises steadily as the distance grows — from 4:48 for the 5 km up to 5:27 for the marathon — which is exactly the gradual slowdown the 1.06 exponent is designed to model.

Common uses

A race time predictor helps whenever you want a number to aim for:

• Setting a marathon goal from a recent 10 km or half, so you start the race at a sensible pace instead of guessing.
• Choosing a target pace for a workout or time trial, using the predicted pace per km as your reference.
• Comparing two races at different distances to see which was your stronger performance once they are scaled to the same yardstick.
• Planning a pacing strategy by converting a goal finish time back into a per-km or per-mile pace.
• Tracking fitness over a season by re-predicting from each new race and watching the projected times drop.

Tips and common mistakes

• Use a recent, all-out race. The prediction is only as good as the input. A 10 km run at training effort will under-read your true potential.
• Keep the distances close. Predicting a 5 km from a 10 km is very reliable; predicting a marathon from a 5 km is a stretch. Riegel himself suggested staying within roughly a four-fold distance range.
• Train for the target distance. A marathon prediction assumes you have the endurance and fuelling to hold the pace for 42.195 km. Without the long runs, expect to finish slower than the formula says.
• Mind your units. Mixing miles and kilometres is fine because the tool converts with 1 mile = 1.609344 km, but make sure each distance is entered in the field you intend.
• Do not treat it as a guarantee. The output is a model, not a promise. Use it as a target band rather than an exact split.
• Effort must match. Riegel assumes equal effort at both distances; comparing a casual jog with a peak race will skew the prediction.

Limitations and notes

Riegel’s formula is a population-average model, not a personalised physiology engine. It does not know your VO₂ max, your fuelling, the course profile, the weather, or how much specific endurance training you have done — all of which move a real finish time. The single 1.06 exponent fits most trained runners well across middle distances, but it tends to read optimistic for the marathon when the known result is a short race, because the marathon adds challenges (glycogen depletion, leg durability) that no short race tests. It also assumes similar effort levels at both distances and is least reliable at the extremes — very short sprints or ultramarathons fall outside the range it was built for. Treat the predicted time and pace as a well-grounded starting point, then adjust with your own experience. Everything is computed privately in your browser, so you can run as many predictions as you like.

For more sports and scorekeeping math, try the golf handicap calculator, the bowling score calculator, or the batting average calculator, and browse the full sports category.