Race Time Predictor
Predict finish times for any distance from a known race result.
Race Time Predictor
Predicts your finish time for any race distance based on a known result. Uses the Riegel formula — the most widely validated endurance performance model.
Riegel formula: T₂ = T₁ × (D₂ / D₁)^1.06. The 1.06 exponent accounts for the fatigue factor — running gets disproportionately harder at longer distances. Accuracy degrades for very short distances (<3 km) or ultra-long events (>50 km). Training and race-day conditions significantly influence actual results.
About this calculator
The Riegel formula (T₂ = T₁ × (D₂/D₁)^1.06) predicts race finish times across distances based on a known performance. The exponent 1.06 reflects the physiological reality that pace slows slightly with distance due to fatigue and aerobic ceiling. It is most accurate for predictions within 2–3x the source distance (e.g., 5K to 10K or 10K to half marathon) and less reliable for extreme extrapolations (e.g., 1 mile to marathon). Race-specific factors like hills, heat, and pacing strategy can cause actual results to deviate by 2–5% from the prediction.
How to interpret your results
The predicted time represents what a physiologically equivalent performance would look like at the target distance — assuming your training specificity matches. If you have been training primarily for 5Ks, a predicted half marathon time based on your 5K will likely be optimistic because you lack the endurance-specific adaptation for the longer distance. Conversely, a marathon-trained runner predicting a 5K will likely outperform the Riegel estimate because their lactate threshold is highly developed. Use the prediction as a target to build training around, not a guaranteed outcome. For race day, aim for even or negative splits (running the second half slightly faster than the first).
The science and formula
The Riegel formula was published by Peter Riegel in American Scientist (1977): T₂ = T₁ × (D₂/D₁)^1.06. The exponent 1.06 was empirically derived from world record progression across distances and reflects the "fatigue factor" — the rate at which running pace slows as distance increases. A value of 1.06 means each doubling of distance increases time by approximately 6% more than simple proportional scaling. The Cameron formula (an alternative) uses a different derivation and produces similar but not identical results, particularly at marathon distance. Both formulas assume optimal pacing and equivalent training preparation.
Important limitations
The Riegel formula becomes increasingly inaccurate for distances more than 3–4× apart from the reference distance. It does not account for: course profile (hills, turns), environmental conditions (heat, altitude), race-day pacing errors, or distance-specific physiological demands (marathon glycogen depletion, ultramarathon factors). It also assumes the athlete is equivalently trained for both distances. A 5K specialist predicting a marathon finish time will typically overestimate their performance by 5–10% because the formula cannot capture the specific aerobic base and fuelling adaptations required for ultra-endurance events.
Frequently Asked Questions
How accurate is the Riegel race time prediction formula?
Riegel predictions are typically within 2–5% for well-trained runners predicting adjacent distances (e.g., 10K from 5K, or half marathon from 10K). Accuracy drops for larger leaps — predicting a marathon from a 5K time has more error. The formula assumes comparable training specificity for both distances.
Why does my predicted marathon time seem slower than expected?
The Riegel formula predicts based on pure physiological scaling. Most runners perform worse than predicted at the marathon due to glycogen depletion at the 30–35 km mark. For experienced marathoners, adding 2–4% to the Riegel prediction often gives a more realistic target time.
Can I use this to set a training pace for my target race?
Yes. Once you have your predicted finish time, divide by the race distance to get your target pace per km or mile. Use this as your race pace goal and structure workouts — threshold runs, tempo intervals — around that pace.
Which input distance gives the most accurate predictions?
The closest comparable distance gives the most accurate result. Using a recent 10K to predict a half marathon is more accurate than using a 5K to predict a marathon. Ideally, use a race result from within the last 4–6 weeks at an effort level of 95–100% to ensure the input reflects current fitness.
Does weather affect how accurate the prediction is?
Yes — if your reference race was run in hot conditions and your target race is cool, you will likely outperform the prediction. Running in temperatures above 15°C slows performance by approximately 0.3–0.4% per degree above the optimal range (8–12°C). A hot-weather reference result will underpredict your potential in cool conditions.
How should I use the predicted time to plan my training?
Back-calculate your training paces from the predicted race pace. Easy runs should be 60–90 seconds per km slower than race pace. Threshold runs at 10–20 seconds per km slower than race pace. Intervals at or slightly faster than race pace. This systems approach, used in the Daniels and Pfitzinger frameworks, structures all training around the goal race pace.
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