Race time predictor.
Enter one recent race - a time you actually ran - and this predictor estimates your times at every standard distance. It runs on Riegel's formula, T2 = T1 x (D2/D1)^1.06, the endurance-aware standard. A 25:00 5K predicts about a 52:07 10K, a 1:55:00 half marathon, and a 3:59:47 marathon. The further you extrapolate, the more your real endurance base decides whether you hit it.
predict your race times
Finish time
Distance unit
| Distance | Predicted time | Pace /km | Pace /mi |
|---|---|---|---|
| 5K your time | 25:00 | 5:00 | 8:03 |
| 10K predicted | 52:07 | 5:13 | 8:23 |
| Half marathon predicted | 1:55:00 | 5:27 | 8:46 |
| Marathon predicted | 3:59:47 | 5:41 | 9:09 |
The row marked your time is the race you entered - every other row is a Riegel prediction. These are equivalent times: the same fitness expressed across distances, the way Jack Daniels' VDOT tables work. For the aerobic-capacity number behind them, run the VO2 max calculator. Predictions past double your input distance - a 5K used to guess a marathon - assume endurance the shorter race never tested, so treat them as an optimistic ceiling.
the short answer
A race time predictor takes one race result and estimates your times at other distances. The workhorse is Riegel's formula: T2 = T1 x (D2/D1)^1.06, where T1 is your known time over distance D1. The exponent 1.06 is the fade factor for longer races. Run a 25:00 5K and Riegel predicts a 10K of 25:00 x 2^1.06 = 52:07.
How a race time predictor turns one result into all the others.
Every distance-to-distance predictor rests on one observed fact: as race distance goes up, average pace slows in a predictable way. Peter Riegel captured it in 1977 with a single power curve. Because the exponent is 1.06 and not 1.0, doubling the distance more than doubles the time - a flat-pace projection (exponent 1.0) would under-predict every longer race. That small 0.06 is the whole endurance story compressed into one number.
The catch is that one number assumes your endurance is already built for the target distance. Predictions stay honest inside roughly half-to-double your input distance. Push past 2x - a 5K used to predict a marathon - and the formula quietly assumes you have the aerobic base and fuelling to hold form for four to eight times as long, which most runners who only race 5Ks do not. That is why a predictor reads as a ceiling under ideal training, not a promise.
What is the Riegel formula and where does it come from?
T2 = T1 x (D2 / D1)^1.06: the time for a new distance equals the known time multiplied by the ratio of the distances raised to the power 1.06. Peter Riegel published the formula in 1981 in American Scientist ("Athletic Records and Human Endurance", volume 69, number 3), fitting record times across distances; the exponent 1.06 is his fatigue factor for running. It is the formula this predictor runs, and the multiplier table lets you apply it by hand: multiply your known time by the number in the row of the distance you want.
| Predict this distance | from a 5K time | from a 10K time | from a half marathon time |
|---|---|---|---|
| 5K | x 1.000 | x 0.480 | x 0.217 |
| 10K | x 2.085 | x 1.000 | x 0.453 |
| Half marathon | x 4.600 | x 2.206 | x 1.000 |
| Marathon | x 9.591 | x 4.600 | x 2.085 |
Source: Riegel, P. S. (1981), Athletic Records and Human Endurance, American Scientist 69(3), 285 to 290. The marathon column runs optimistic for most runners, as the section above explains.
Riegel, VDOT and Cameron in one honest paragraph.
Riegel is not the only model. Jack Daniels' VDOT tables map a race result to an aerobic-fitness score and read equivalent times off that curve; they behave much like Riegel for common distances but are tuned from real runner data rather than a single exponent. Dave Cameron's formula adds a distance-dependent term that many runners find more accurate for the marathon specifically. In practice the three agree closely for 5K-to-half predictions and diverge most at the marathon. For the aerobic-capacity side of the same estimate, our VO2 max calculator turns a field-test effort into ml/kg/min, and the running pace calculator breaks any predicted time into even splits.
This tool uses Riegel because it needs a single input, applies cleanly across every distance, and does not hide a lookup table you cannot inspect. When two models disagree on your marathon, trust the one built on the closest input - a half-marathon prediction beats a 5K prediction every time.
Why marathon predictions run optimistic.
The marathon row is the one to distrust. Riegel, VDOT and Cameron all extrapolate from shorter, faster efforts, and the marathon punishes everything the math cannot see: glycogen depletion, the wall, pacing errors, heat and hills. A runner who nails a 45:00 10K has proven a 45-minute engine, not the three-and-a-half hours of fuelling and durability a 3:27 marathon demands. Treat every marathon prediction as your best case on a good day with the long-run volume already in the bank - then add a few honest minutes. The fix is to feed the predictor your most recent long race: a half marathon predicts the marathon far better than a 5K ever will.
A predictor read in reverse sets the whole week.
Coaches use a predictor backwards. The output is not just a finish-time fantasy - the equivalent times set training paces. A client's predicted 10K pace becomes their threshold work, the predicted marathon pace becomes long-run goal pace, and easy runs sit well below all of it. Re-run the predictor off a fresh time trial every training block and the paces move with the athlete instead of going stale. The block after the goal marathon is the one the predictor cannot set - for that, our guide to programming a client's post-marathon recovery lays out the reverse-taper return-to-run before the next block of pace work begins.
Doing that for a full client list is the actual work. Inside Coachway, a coach logs each client's latest race, sets their paces from it, and programs the block where the client's training, check-ins and messages already live - one tab per client instead of a spreadsheet and a chat app. When the next time trial lands, the new paces drop straight into the plan.
Set race paces for your whole client list from one tab.
No charge today - cancel anytime under Billing.Turn the prediction into training paces
Paste the predictions and the pace rows and the model gives the easy, threshold and interval paces for the target race with the page's own marathon caveat; the predictions stay as calculated. The paces feed the running pace calculator.
Turn the prediction into training paces
When to use it: When you plan a client's block for a target race.
What to paste in: The predictions, the target race and weeks, the pace rows, a client ID.
This race time predictor takes a [DISTANCE] time of [TIME] and predicts [PREDICTED 5K] for 5K, [PREDICTED 10K] for 10K, [PREDICTED HALF] for the half and [PREDICTED MARATHON] for the marathon. The client is training for the [TARGET RACE] in [WEEKS] weeks. From the predicted time for that race, give me the easy, threshold and interval paces per km using the pace table on the page ([PASTE THE PACE ROWS]), and a one-line honesty note on the marathon prediction from the page's own caveat. Do not change the predictions. Do not change the calculator's numbers; do not add medical advice; if anything needed is missing, ask me before assuming. Client ID [ID], no name.
The exact math, and its honest limits.
This tool uses Riegel's formula, T2 = T1 x (D2/D1)^1.06, with distances normalised to metres (5K = 5,000 m, 10K = 10,000 m, half marathon = 21,097.5 m, marathon = 42,195 m; a mile is 1,609.344 m). The exponent 1.06 is Riegel's published fatigue factor for runners - a value of 1.0 would mean pace never fades, which no distance runner matches. Pace per kilometre is the predicted time divided by the distance in kilometres; pace per mile divides by 1.609344.
The predictions assume even effort, specific endurance for the target distance, and comparable conditions - flat, measured, temperate. They are estimates for planning, not guarantees, and they say nothing about whether your training supports the number. The honest use is to set targets and training paces from your closest recent race, then let real sessions correct them.
Frequently asked questions.
How does a race time predictor work?
A race time predictor takes one race you have run and estimates your times at other distances. This one uses Riegel's formula, T2 = T1 x (D2/D1)^1.06: it scales your known time by the ratio of the two distances, raised to the power 1.06 so longer races fade slightly. Enter a 25:00 5K and it predicts a 52:07 10K and a 1:55:00 half marathon.
How accurate is the Riegel race predictor?
It is accurate to within a couple of percent when you predict across nearby distances - a 10K from a 5K, say - and you have actually trained for the target distance. Accuracy falls as the gap between the input and target grows, because the formula assumes endurance the shorter race never tested. Predict inside roughly half-to-double your input distance and read anything beyond that as an optimistic ceiling.
Can I predict a marathon time from a 5K or 10K?
You can, but read it as a best case. A 20:00 5K predicts a 3:11:49 marathon by Riegel, yet that number assumes the aerobic base, long-run volume and fuelling to hold pace for eight times the distance. Most runners who only race 5Ks have not built that, so their real marathon comes in slower. A recent half marathon gives the most trustworthy marathon prediction.
What is the exponent 1.06 in Riegel's formula?
The 1.06 is Riegel's fatigue factor - the exponent that makes time grow slightly faster than distance. If it were 1.0, the predictor would assume you hold the exact same pace forever, so doubling the distance would exactly double the time. Real runners slow as races lengthen, and 1.06 captures that fade across the common road distances. A larger exponent would predict a steeper slowdown.
How do coaches use a race time predictor to set training paces?
They run it in reverse. The equivalent times a predictor produces are pace targets: predicted 10K pace anchors threshold work, predicted marathon pace becomes long-run goal pace, and easy days sit well below both. Re-testing with a fresh time trial each training block keeps those paces honest as the athlete changes, rather than programming off a race from six months ago.
Where does the Riegel formula T2 = T1 x (D2/D1)^1.06 come from?
From Peter Riegel's 1981 article Athletic Records and Human Endurance in American Scientist (volume 69, number 3), which fitted record performances across distances and found time rising with distance to the power of about 1.06 for running. The predictor on this page uses that exponent unchanged; the multiplier table above gives the factor between any two of the four common distances so the formula can be applied by hand.
Can ChatGPT turn a race prediction into training paces?
It can derive easy, threshold and interval paces for the target race from the predicted time and the pace rows on this page, and repeat the marathon caveat. It cannot judge the client's aerobic base, which is why the predictor reads optimistic for the marathon; the prompt keeps the predictions unchanged.
Every predicted time is an estimate from one race under ideal training, not a guarantee - the marathon row is the least certain. Maximal race efforts suit runners cleared for hard training; this tool is general fitness information, not medical advice.
Keep building the plan: the running pace calculator turns any predicted time into splits in min/km and min/mi, the VO2 max calculator estimates the aerobic engine behind these times from a field test, and the heart rate zone calculator sets the intensity for each run.
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This predictor handles one runner at a time. Coachway lets a coach log each client's latest race, set their training paces from it, and program the block next to the client's check-ins and messages - one tab, not six. Built on knowledge from working with 150 online coaches over 6+ years.
