Estimate Your 10K Time Based on Your 5K Performance 🌎

How It's Calculated

The Riegel formula predicts race times across distances using a single fatigue exponent derived from empirical data across hundreds of athletes:

T2 = T1 × (D2 / D1)^1.06

Where:
  T1  = your known race time (in seconds or decimal minutes)
  D1  = distance of the known race (5 km)
  D2  = target distance (10 km)
  D2/D1 = 10/5 = 2.0
  2.0^1.06 ≈ 2.0849

So: T2 = T1 × 2.0849

Example: T1 = 25:00 = 1500 seconds
  T2 = 1500 × 2.0849 = 3127.4 seconds ≈ 52:07
  (Rounded to 52:16 when accounting for full HH:MM:SS conversion)

The multiplier 2.0849 is fixed for the 5K→10K projection. A "pure double" would give 2.0000×, meaning the Riegel model predicts you'll run the 10K about 4.2% slower per kilometer than your 5K pace — a well-documented aerobic fatigue effect.

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Reference Table

> All predictions assume the 5K was run on a flat, comparable course in similar conditions. Heat, elevation, and fatigue can shift results by ±2–5%.

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Typical Use Cases (With Numbers)

Case 1 — Recreational Runner, 5K in 25:00:
Using the formula: 1500 s × 2.0849 = 3127 s = 52:07. This runner should target a 10K pace of approximately 5:13/km (8:23/mile). If they ran their 5K all-out on a flat course in mild weather, 52:07–52:30 is a solid, realistic goal.

Case 2 — Intermediate Runner, 5K in 20:00:
1200 s × 2.0849 = 2501.9 s = 41:42. Target 10K pace: 4:10/km (6:42/mile). At this level, aerobic capacity is well-developed, so the Riegel prediction tends to be quite accurate (within ±30 seconds for well-trained runners).

Case 3 — Beginner Runner, 5K in 35:00:
2100 s × 2.0849 = 4378.3 s = 72:58 ≈ 1:12:58. Target pace: 7:18/km (11:45/mile). Beginners often slow more than the model predicts due to lower lactate threshold development, so treating the result as a "best-case" ceiling is advisable.

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Common Mistakes

1. Using a training run instead of a race effort — The Riegel formula requires a maximal race effort. A comfortable training 5K at 27:00 will produce an optimistic 10K prediction; your race 5K might be 25:00, giving a very different target.

2. Ignoring course differences — A hilly 5K course will produce a slower time than your flat fitness warrants. Plugging a hillier 5K time into the formula will underestimate your 10K potential on a flat course.

3. Assuming the prediction is pace-agnostic — The formula predicts finish time, not a steady pace guarantee. Going out too fast in the first 4K of a 10K will cause the second half to blow up well beyond the predicted split.

4. Applying it across very different distances — Riegel's exponent (1.06) is most accurate for distances between 1.5 km and the marathon. Using a 1-mile time to project a 10K introduces larger error margins.

5. Not accounting for fitness staleness — If your 5K result is older than 8–10 weeks, significant fitness changes (positive or negative) may make the prediction unreliable.

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