How accurate is the race time predictor?

Riegel's formula is most accurate when the target distance is within roughly 2 to 3 times the distance of your input race. Predicting a marathon from a 5K tends to be optimistic because endurance, fueling, and pacing matter more over longer distances.

What is Riegel's formula?

It is an empirical endurance model: T2 = T1 × (D2 / D1) ^ 1.06. The 1.06 exponent captures how pace slows as distance grows. It was derived by Pete Riegel from large sets of race results.

Why is my predicted marathon time slower than a simple pace multiply?

Because the formula accounts for fatigue. Holding 5K pace for a marathon is impossible for almost everyone, so the 1.06 exponent stretches the predicted time beyond a linear extrapolation.

Can I use a training run instead of a race?

You can, but predictions assume a near-maximal effort. A relaxed training run will under-represent your race fitness and give pessimistic predictions, so use a genuine time-trial or race result for best accuracy.

Does it work in miles?

The math is unit-independent because it uses the ratio of distances. The presets include both metric and imperial distances (1 mile, 10 mile), and paces are shown per kilometre.

What is the Running Race Time Predictor?

Free running race time predictor using Riegel's formula. Enter a recent race result and instantly forecast your 5K, 10K, half marathon, and marathon finish times and paces. Runs in your browser. It runs free in your browser on Gera Tools, with nothing uploaded.

Running Race Time Predictor

Name: Running Race Time Predictor
Creator: Gera Tools
License: https://creativecommons.org/licenses/by/4.0/

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Running race time predictor

This tool forecasts your finish time at popular race distances from one recent result. It is built on Riegel’s running formula, an empirical relationship that fits the way nearly every runner slows as distance increases. Enter a 5K and instantly see realistic 10K, half marathon, and marathon targets — useful for goal setting, pacing, and choosing a realistic A-goal on race day.

How it works

The predictor applies Riegel’s equation:

T2 = T1 × (D2 / D1) ^ 1.06

T1 is your known time over distance D1, and T2 is the predicted time over the target distance D2. The exponent 1.06 is the key: if pace were constant it would be 1.0, but real runners fatigue, so each doubling of distance costs slightly more than double the time. The tool converts every distance to metres internally, computes the ratio, raises it to the 1.06 power, and formats the result.

Tips and accuracy notes

Predictions are most reliable within a 2–3× distance range of your input race.
Marathon predictions from short races are usually optimistic — your real result depends on long-run training, fueling, and heat.
Re-run the tool with a fresh result every few weeks to track fitness changes.

Worked example: 5K to marathon

Suppose you recently ran a 5K in 22:30 — a solid training race at genuine effort. Applying Riegel’s formula:

For a 10K prediction: T2 = 22:30 × (10000 / 5000) ^ 1.06 ≈ 22:30 × 2.085 ≈ 46:55. For a half marathon: the ratio (21.0975 / 5) to the power 1.06 stretches the time further. For a full marathon: the 8.44× distance ratio, raised to 1.06, gives a multiplier around 9.27, so a 22:30 5K predicts roughly a 3:28:30 marathon.

The 5K to marathon gap is large and the prediction should be treated as an optimistic target — marathon performance adds endurance-specific demands (glycogen, heat management, long-run training volume) that a single 5K cannot capture. Use the 10K prediction more confidently, and the half-to-full prediction more confidently still.

How to use predictions for goal setting

Setting a race goal. Use the predicted time as an A goal — the time you would run on a perfect day. Build B and C goals 2–5 minutes slower per race. Running at exactly your predicted marathon pace early in a race when you have not done the requisite long runs is the classic way to blow up at mile 20.

Tracking fitness changes. Run the tool from a fresh race result every few weeks of structured training. If your 5K time improves, all the longer-distance predictions tighten with it. The rate of improvement tells you whether training is working.

Comparing across distances. If your 5K predicts a different marathon than your half-marathon predicts, the shorter-distance number reflects your top-end speed and the longer-distance number reflects your aerobic endurance. A gap suggests which system to prioritise in training.

Everything runs locally in your browser — nothing is uploaded.