Race Time Predictor

Race Time Prediction Guide

What do I need to know about Riegel's Formula?

Riegel's formula (1977) predicts race times: T2 = T1 × (D2/D1)^1.06. Where T1 is your known time over distance D1, and you are predicting T2 over distance D2. The exponent 1.06 reflects the fact that performance degrades slightly at longer distances — you cannot simply scale by distance because fatigue increases non-linearly with distance. The formula is most accurate for distances within 3–5× of your reference race. Predicting a marathon from a 5K has more uncertainty than predicting a 10K from 5K, since fatigue and pacing become bigger factors over longer distances.

Why Predictions Have Uncertainty?

Riegel's formula assumes you are equally trained for both distances. In practice: runners with more endurance training do better than predicted at longer distances. Runners with more speed work do better at shorter distances. The formula works best when comparing similar distances (5K→10K, or 10K→half marathon). Marathon prediction from a 5K can easily be 10–20 minutes off. Factors that affect race outcome beyond fitness: heat and humidity (slows marathon runners more than 5K runners), course hills, poor pacing early in the race, and how well the taper before race day was managed.

What do I need to know about Using Predictions Wisely?

Treat predicted times as a training guide and pacing target, not a guarantee. For your first race at a new distance, start 5–10% slower than predicted pace and negative-split (run the second half faster than the first). More experienced runners can target predicted pace from the start. Predictions are most useful for setting a training goal: if you want to run a 1:45 half marathon and your current 10K is 50 minutes, Riegel predicts 1:48 — you need to improve your 10K by 2–3 minutes first.

What's the key thing to understand about Race-Specific Training?

The prediction assumes your fitness transfers across distances. To validate the prediction, your training should include: long runs at easy pace building to 75–80% of race distance (for marathon: long runs of 30–32km). Race-pace training: intervals and tempo runs at predicted race pace. For marathons specifically: running 80–160km/week (serious amateurs) is associated with times within 5% of Riegel prediction. Running less mileage than a distance demands results in finishing slower than predicted.

What's the key thing to understand about Riegel's Formula?

Most race time prediction calculators, including common online tools, are based on Riegel's formula, developed by exercise scientist Pete Riegel in 1977: T2 = T1 × (D2/D1)^1.06, where T1 and D1 are a known time and distance, and T2 is the predicted time for a new distance D2. The exponent of 1.06 (rather than exactly 1.0) reflects the well-established fact that pace naturally slows as race distance increases — running twice the distance takes more than twice as long for virtually every runner, because longer efforts draw more heavily on endurance capacity and are more affected by glycogen depletion and accumulated fatigue, rather than being a simple linear scaling of pace. Riegel derived the 1.06 exponent from analysing a wide range of real running (and other endurance sport) performance data across different distances, and it has held up reasonably well over decades of subsequent use, especially for predicting between middle-distance and longer events (such as predicting a marathon time from a 10K or half marathon result) run by a reasonably well-trained endurance athlete. The formula is intentionally simple — using only one known performance and a fixed exponent — which is both its main strength (easy to apply with minimal data) and its main limitation, since it cannot account for an individual's specific strengths or weaknesses across different distances.

What do I need to know about Why Longer Races Don't Scale Linearly?

Riegel's 1.06 exponent exists because the physiological demands of distance running change meaningfully as race length increases, and no single pace-scaling factor is perfectly accurate for every runner or every distance jump. Short, fast races (5K and under) rely heavily on anaerobic capacity and lactate threshold, while marathon and ultra-distance events rely much more on aerobic endurance, fat utilisation efficiency, glycogen management, and fuelling strategy — qualities that don't necessarily scale together in the same person. This is why Riegel-based predictions tend to be noticeably less accurate the larger the gap between the known and predicted distances (predicting a marathon time from a 5K result is considerably less reliable than predicting it from a half marathon result, since the half marathon shares more physiological demands with the marathon), and why the formula is particularly prone to overestimating marathon performance for runners who haven't built adequate long-run endurance and fuelling strategy specifically for that distance, since a formula based purely on shorter-distance speed cannot detect an endurance or fuelling limitation that only shows up beyond around 2-3 hours of continuous effort. Experienced coaches generally treat Riegel-based predictions as a reasonable starting estimate for a well-trained, appropriately-prepared runner, but expect the formula to be considerably less reliable for anyone whose training hasn't specifically prepared them for the demands of the target race distance.

Should You Predict From a Recent Race or a Time Trial?

Both a recent race and a solo time trial can feed a performance predictor, but they carry different strengths and weaknesses worth understanding. A genuine race typically produces a more reliable predictor of fitness because competition brings out effort levels that are very difficult to replicate alone — the presence of other runners, a clear finish line, and the psychological lift of race-day atmosphere all tend to push effort closer to true maximum than most people can manage in a solo effort, even when trying hard. A solo time trial, run alone against the clock with no competitors, often comes in somewhat slower than true current fitness for exactly the opposite reason — without external pacing cues or competitive pressure, many people unconsciously hold back, producing a predictor that understates actual race potential. That said, a time trial has real advantages: it can be scheduled precisely when needed for training feedback rather than waiting for a race calendar to line up, it avoids the taper and recovery cost of an actual race, and it can be repeated at controlled intervals to track trend. For the most reliable single prediction, a recent genuine race result, ideally over a distance reasonably close to the target race, is generally the better input; for ongoing training feedback between races, a consistent, honestly-paced time trial protocol — even if it reads a touch conservative — is a practical and lower-cost substitute.

A Quick Sanity Check Before Trusting a Prediction

Riegel-style predictions are most reliable when the reference race and the target race are reasonably close in distance — typically within about a 2-3x range (predicting a half marathon from a recent 10K, for example, works better than predicting a marathon from a recent 5K), because the fatigue and pacing factors that differ between short, middle and ultra-distance events compound the further apart the two distances are. If your reference time is several months old, from a very different training block, or was run in unusually hot or hilly conditions, treat the predicted time as a rough planning guide rather than a firm target, and prioritise a fresher time trial under similar conditions to the target race whenever one is available.

Worked Example: Predicting a 10K Time From a Recent 5K

Say a runner has just completed a 5K in 24:00 (1440 seconds) and wants to estimate their 10K potential. Riegel's formula is T2 = T1 x (D2/D1)^1.06, where D2/D1 is the distance ratio of 2. First calculate 2^1.06, which comes out to roughly 2.085. Multiplying 1440 seconds by 2.085 gives approximately 3,002 seconds, or 50 minutes and 2 seconds. That is the predicted 10K time if fitness and pacing execution are comparable between the two efforts. Notice this is noticeably slower than simply doubling the 5K time (which would give 48:00), because the exponent above 1.0 accounts for the extra fatigue that accumulates over the longer distance. Riegel's formula works best for predicting distances within about 2-3x the reference race; using a 5K to predict a marathon (an 8.4x jump) stretches well past where the model stays reliable, and the real result will usually be slower than the formula suggests once aerobic endurance and fuelling become limiting factors rather than raw speed.