Race Time Predictor
Predict your finish times for any race distance using the Riegel formula. Enter a known result and get predictions for 5K, 10K, half marathon, and marathon.
This race time predictor uses the Riegel formula to estimate your finish times across a range of distances. Enter a recent race result - any distance from 1K to a marathon - and see predicted times, paces, and speed for 1K, 5K, 10K, half marathon, marathon, and 50K ultra distances. The default fatigue exponent of 1.06 matches the original 1977 Runner's World publication, and can be tuned between 1.04 and 1.10 to match your individual drop-off curve.
For informational purposes only. Not a substitute for professional medical advice. Consult a healthcare provider before making changes to your diet or exercise routine.
About Race Time Predictor
The Riegel Formula
American research engineer Peter Riegel (1935-2018) published this formula in a 1977 Runner's World article. It remains one of the most widely used race prediction models more than four decades later. The formula is:
T2 = T1 x (D2 / D1) ^ 1.06
| Variable | Meaning |
|---|---|
| T1 | Your known race time |
| D1 | The distance of your known race |
| T2 | Predicted time for the target distance |
| D2 | The target distance |
| 1.06 | The fatigue exponent (adjustable) |
The exponent of 1.06 means that doubling the distance increases your time by slightly more than double, capturing the natural slowdown from fatigue, glycogen depletion, and accumulated muscle damage. Riegel validated the model across running, swimming, and walking events lasting roughly 3.5 to 230 minutes - which conveniently covers 1500m through the marathon for most runners.
Worked example: Suppose you ran a 10K in 45:00 (45 x 60 = 2,700 seconds) and want to predict your marathon time. T2 = 2,700 x (42.195 / 10) ^ 1.06 = 2,700 x 4.2195 ^ 1.06 = 2,700 x 4.607 = 12,440 seconds, which is 3 hours, 27 minutes, 20 seconds. The Riegel prediction assumes marathon-specific training; a 10K runner without long-run miles will typically finish slower than this.
Adjusting the Fatigue Exponent
The 1.06 exponent is a population average. Individual physiology, training history, and distance ratio all affect how much your pace drops at longer distances. Tune the exponent based on your own past race data.
| Exponent | Runner Type | When to Use |
|---|---|---|
| 1.04-1.05 | Elite / highly trained | Runners with strong aerobic base who maintain pace well over distance |
| 1.06 (default) | Competitive recreational | Most runners with consistent training and some race experience |
| 1.07-1.08 | Less trained / newer runners | Runners who slow down more at longer distances due to lower aerobic fitness |
| 1.09-1.10 | Undertrained for distance | Runners predicting a much longer distance than they have raced |
Dave Cameron's formula, an alternative built from a large empirical dataset of race results, uses an adaptive exponent (around 1.07 for shorter jumps and 1.05 for marathon predictions). If your last three races all came in slower than the Riegel prediction, try nudging the exponent up by 0.01 at a time until the formula matches reality.
Example Predictions
Based on a 25:00 5K (5:00/km pace) with the standard 1.06 exponent:
| Distance | Predicted Time | Predicted Pace (min/km) | Predicted Pace (min/mile) |
|---|---|---|---|
| 1K | 4:32 | 4:32 | 7:18 |
| 5K | 25:00 (input) | 5:00 | 8:03 |
| 10K | 52:07 | 5:13 | 8:23 |
| Half marathon | 1:55:00 | 5:27 | 8:46 |
| Marathon | 3:59:47 | 5:41 | 9:09 |
| 50K | 4:47:02 | 5:44 | 9:14 |
Notice how pace per kilometre increases (slows) at each distance step. This is the fatigue effect the formula captures. The jump from 5K to marathon pace is about 41 seconds per kilometre - roughly 14% slower - which matches what exercise physiologists observe in the field.
How Accurate Are Race Predictions?
| Prediction Type | Accuracy | Notes |
|---|---|---|
| 5K to 10K | Very good (within 1-2%) | Similar energy systems, small distance jump |
| 10K to half marathon | Good (within 2-3%) | Moderate extrapolation, reliable for trained runners |
| Half marathon to marathon | Reasonable (within 3-5%) | Marathon-specific training matters a lot; fuelling becomes a factor |
| 5K to marathon | Rough estimate (5-10%) | Large extrapolation; many additional factors at marathon distance |
| Any to ultra (50K+) | Approximate only | Terrain, nutrition, sleep, and pacing strategy dominate at ultra distances |
The closer the distances, the more accurate the prediction. For the best marathon prediction, use a half marathon result. For the best half marathon prediction, use a 10K result. Research published in PLOS One on power-law models of running performance suggests individual runners do not follow a single universal exponent, which is why exposing the factor as an adjustable input matters for honest predictions.
The Riegel formula tends to predict overly optimistic times at both ends of its range - for efforts under about five minutes (where anaerobic metabolism dominates) and for marathons run without specific long-distance preparation (where glycogen depletion kicks in). A useful cross-check is to compare the Riegel output against a VDOT prediction from Jack Daniels' Running Formula; if they agree, trust the number, and if they diverge, your actual performance is likely somewhere between them.
Coaching resources such as RunnersConnect estimate that roughly 80% of recreational runners fail to hit the marathon time their short-race PRs suggest, usually because training volume does not match the prediction. The formula describes a physiologically possible outcome for a runner who has done the work - it is not a guaranteed race-day ceiling.
Where Real Runners Finish (2024-2025 Data)
Use these reference figures to sanity-check your prediction against the wider running population. All figures come from published race analyses covering the most recent completed race season.
| Distance | Cohort | Average Finish | Source |
|---|---|---|---|
| 5K (parkrun global) | All finishers, 2,600+ events | 32:00 | parkrun HQ |
| 5K (parkrun UK) | All UK finishers | 28:58 | parkrun HQ |
| 5K (parkrun USA) | USA finishers, Aug 2025 | 34:17 | parkrun HQ |
| Half marathon (US, men) | 2024, ~1M finishers | 1:55:26 | RunRepeat |
| Half marathon (US, women) | 2024, ~1M finishers | 2:11:57 | RunRepeat |
| Marathon (US, overall) | 2024, ~97% of US races | 4:34 | RunRepeat |
| Marathon (US, men) | 2024 | 4:24 | RunRepeat |
| Marathon (US, women) | 2024 | 4:51 | RunRepeat |
For context, the 2024 US marathon average of 4:34 was 1.9% faster than 2019, the first multi-year improvement in several decades according to RunRepeat's State of US Marathons analysis. About 45% of half marathon finishers in the US break the two-hour barrier. parkrun average times in the UK (28:58) have drifted slower every year for 16 consecutive years as the event has grown to include more walkers and first-time runners; raw participation has climbed from around 41,000 weekly finishers in 2012 to 360,000-390,000 across 20 countries in late 2025. If your prediction lands inside one of these ranges, it is a statistically realistic target for your demographic.
Race Distance Reference
| Distance | Kilometres | Miles | Typical Recreational Time Range |
|---|---|---|---|
| 1K | 1.0 | 0.62 | 3:30 - 7:00 |
| 5K | 5.0 | 3.11 | 18:00 - 40:00 |
| 10K | 10.0 | 6.21 | 38:00 - 85:00 |
| Half marathon | 21.0975 | 13.11 | 1:20 - 3:00 |
| Marathon | 42.195 | 26.22 | 2:50 - 6:00+ |
| 50K ultra | 50.0 | 31.07 | 3:30 - 8:00+ |
Alternative Prediction Models
The Riegel formula is the most common predictor because it needs only one past race and one exponent. Several other methods exist, each with trade-offs:
| Method | How It Works | Strengths |
|---|---|---|
| Riegel (1977) | Single power-law exponent applied to distance ratio | Simple, transparent, works across sports |
| VDOT (Daniels, 1998) | Pseudo-VO2max index combining aerobic capacity and running economy | Also outputs training paces for intervals, tempo, easy runs |
| Cameron formula | Empirical coefficients with distance-dependent exponent | More conservative for marathon predictions |
| Yasso 800s | 10 x 800m workout time in mm:ss predicts marathon in hh:mm | Training-based cross-check, popular among recreational marathoners |
| Jeff Galloway Magic Mile | Single-mile time trial applied to empirical conversion factors | Built on 300,000+ runner dataset across 40 years |
Former Runner's World chief running officer Bart Yasso popularised the 800m workout as an informal marathon predictor, though no peer-reviewed study has validated it. Most serious coaches use Riegel or VDOT as the baseline and adjust based on specific workout performances during the training block. In practice, a runner entering a marathon build will often run a tune-up half marathon six to eight weeks out, plug that time into Riegel, and use the resulting marathon prediction as the start of their goal pace work. Matching the predicted pace for long intervals (say 4 x 2 miles with short recovery) is a stronger signal than the formula output alone.
Tips for Using Race Predictions
| Tip | Why |
|---|---|
| Use a recent result (within 4-6 weeks) | Fitness changes over time; an old race time may not reflect current ability |
| Use a race, not a training run | You run faster in races due to adrenaline, competition, and proper tapering |
| Choose the closest distance available | Predicting 10K from a 5K is more reliable than predicting a marathon from a 5K |
| Account for course difficulty | Hilly or trail courses are slower than flat road courses; adjust expectations |
| Train specifically for the target distance | The formula assumes adequate training - you cannot race a marathon on 5K fitness alone |
| Factor in weather and heat | Every 5C above 13C slows marathon pace by roughly 2-3% for recreational runners |
| Re-run the prediction after each tune-up race | Multiple recent data points sharpen the estimate and reveal your personal exponent |
For detailed pace and split planning at your predicted time, use the pace calculator. To estimate the energy cost of your race, the calories burned calculator covers running at various intensities. Runners dialling in aerobic training zones should also check the target heart rate calculator to match workout effort to predicted pace. All calculations run in your browser with no data stored.
Sources
Frequently Asked Questions
What is the Riegel formula?
The Riegel formula (T2 = T1 x (D2/D1)^1.06) predicts race times by accounting for the fact that your average pace naturally slows as distance increases. The exponent of 1.06 models the typical fatigue effect. It was developed by Pete Riegel and published in 1977.
How accurate are the predictions?
The Riegel formula is reasonably accurate for distances between 1500m and the marathon, especially for well-trained runners. Predictions become less reliable at extreme distances (ultras) or for very short races. Your actual performance also depends on training, course conditions, weather, and race-day strategy.
What exponent should I use?
The standard exponent is 1.06 and works well for most recreational and competitive runners. Elite runners who maintain pace better over distance might use 1.04-1.05. Less trained runners who slow more at longer distances might use 1.07-1.08. Experiment to see what matches your past results.
Can I use a 5K time to predict a marathon?
Yes, but the further apart the distances, the less precise the prediction. A 10K time is a better predictor for a half marathon than a 5K time. For the most accurate marathon prediction, use a half marathon result as your known time.
Why does pace increase at longer distances?
As distance increases, your body shifts more to aerobic energy systems, glycogen stores deplete, and muscular fatigue accumulates. The Riegel exponent captures this predictable slowdown. That is why a 10K pace is always slower than a 5K pace, even on the same day.
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