What is the Riegel formula?

T2 = T1 × (D2 ÷ D1)^1.06. It scales a known race time up or down to a new distance using a fixed fatigue exponent of 1.06.

Why is the exponent 1.06 and not 1?

An exponent of 1 would mean you hold the exact same pace at any distance, which is impossible. Riegel fitted real race data and found pace slows just enough that doubling the distance multiplies time by about 2^1.06 ≈ 2.08.

Is Riegel accurate for the marathon?

Less so. Predicting a marathon from a short race tends to overestimate your ability because the marathon is limited by endurance, fueling and muscular fatigue that short races don't expose. Treat long-distance predictions as optimistic targets that assume marathon-specific training.

Riegel race-time prediction explained

If you have one recent race result, you can predict your time at other distances with surprising accuracy using a formula Pete Riegel published in 1981. Here is how it works and when to trust it.

The answer first

Riegel’s model is:

T2 = T1 × (D2 / D1)^1.06

where T1 and D1 are your known time and distance, and D2 is the distance you want to predict. Our race time predictor applies it to project your 5K, 10K, half-marathon and marathon from a single result.

Where the 1.06 comes from

If you could hold the same pace at every distance, the exponent would be exactly 1 and time would scale linearly with distance. In reality pace slows as races get longer — you simply cannot sustain 5K pace for a marathon. Riegel analysed race data across events and found the relationship is captured well by an exponent of 1.06. That means doubling the distance multiplies your time by about 2^1.06 ≈ 2.08, not 2.

A worked example

Suppose you run a 5K in 22:00 (1320 seconds). Predicting the half-marathon (21.0975 km):

T2 = 1320 × (21.0975 / 5)^1.06
   = 1320 × (4.2195)^1.06
   ≈ 1320 × 4.60
   ≈ 6072 seconds
   ≈ 1:41:12

Here is the full projection from that 5K:

Distance	Predicted time	Pace /km
5K	22:00	4:24
10K	45:52	4:35
Half marathon	1:41:12	4:48
Marathon	3:31:00	5:00

Notice the pace per km slows at every step up — that is the 1.06 exponent at work.

When it is accurate (and when it isn’t)

Riegel works best when:

The predicted distance is reasonably close to the known one (e.g. 10K from a 5K).
You are equally trained for both distances.

It is least accurate predicting a marathon from a short race, because the marathon is limited by glycogen depletion, fueling and muscular durability that a 5K never tests. A 5K-based marathon prediction is best read as “the time you could run if you also did the long runs and fueling practice.”

Using your predictions

Once you have a target time, turn it into per-km and per-mile splits with the running pace calculator, and pace your effort by feel using the heart-rate zone calculator.

Bottom line

Riegel is a simple, durable model that gets you a realistic target from one race. Trust it most for nearby distances, treat marathon predictions from short races as optimistic, and always pair the number with the right training.

General training information only, not individualised coaching or medical advice.