Methodology & sources

What the labels mean

Model

A number calculated by our models below, such as expected time, pace, speed or watts.

Research

The direction of the advice is supported by a cited study.

Coaching tip

Common coaching advice. Sensible, but not a research finding.

Split strategies

Pacing strategies are commonly described as even, negative, positive and variable. For endurance events, a fairly even distribution tends to give better times (Abbiss & Laursen 2008).

Our choice: the pacing slider changes your target pace in a straight line over the distance. The percentage is how much faster (negative split) or slower (positive split) the second half is than the first. Your goal time never changes.

Reading your course file

Distances between points use the haversine formula (explainer).

Our choices, needed because GPS and map elevation data are noisy:

• The course is resampled every 10 m.
• Single-point spikes are removed, then elevation is smoothed over about 150 m.
• Climbing is only counted once a rise passes 2 m, so small wobbles don't add up.
• A climb is a rise of at least 10 m with an average gradient of at least 2%. Dips under 5 m don't end a climb.

That's why our total climbing can differ from your watch or Strava: every service smooths elevation differently.

Running on hills

Minetti and colleagues measured the energy cost of running on gradients from −45% to +45% (Minetti et al. 2002):

Cr(i) = 155.4i⁵ − 30.4i⁴ − 43.3i³ + 46.3i² + 19.5i + 3.6   (J·kg⁻¹·m⁻¹)

where i is the gradient as a decimal (0.05 = 5%).

Our choices:

• At constant effort, your pace on a gradient is your flat pace × Cr(i) / Cr(0).
• Downhill gains are capped at 12% faster than flat pace. The equation alone predicts unrealistically fast descents; real runners are limited by their legs and footing.
• Sections steeper than 15% are flagged: power-hiking may cost little time there.

Cycling on hills

The power needed at a given speed is the sum of air drag, rolling resistance and gravity. This model was validated against on-road power-meter data (Martin et al. 1998):

P = [ ½·ρ·CdA·v³ + Crr·m·g·cos θ·v + m·g·sin θ·v ] / η

Riding slightly harder uphill and easier downhill is faster than constant power for the same overall effort (Swain 1997). Our choice: "Push the climbs slightly" adds up to 8% power uphill (full effect from 4% gradient) and takes the same off downhill. The default is even effort, which protects your run.

Speed mode (default) keeps your goal time and uses the model only to spread it over the course; no watts are shown. Power mode (experimental) predicts your bike time from your power and the values above. Real CdA varies a lot, so treat it as a rough guide.

How terrain becomes splits

1. The course is cut into 100 m pieces, each with its own gradient. If the file is a bit shorter or longer than the race, it's stretched to fit.
2. Each piece gets a time from the running or cycling model above. Swims stay flat.
3. Your split strategy is applied on top.
4. Everything is scaled so the leg takes exactly your goal time (or the predicted time in power mode).
5. The pieces are added up into the splits you see: per km or mile for running, every 5–10 km for cycling.

Finish-time prediction

To predict a time from one benchmark result we use Riegel's endurance formula (Riegel 1981):

T₂ = T₁ × (D₂ / D₁)^b

with Riegel's own exponents per sport: running 1.07732 (men) / 1.08283 (women), swimming 1.02977 / 1.03256, cycling 1.04834. Riegel found the relationship holds for efforts of roughly 3.5 to 230 minutes, so predictions for longer legs, like a full-distance bike or run, are less certain.

Critical swim speed

Critical speed is the slope of the distance–time line for all-out swims over several distances, and pool critical speed tracks 400 m race speed very closely (Wakayoshi et al. 1992). With two swims the slope is simply:

CSS = (D_long − D_short) / (T_long − T_short)

Coaching practice, not research: the 400 m + 200 m test and the training zones around CSS (easy +10–15 s, endurance +5–10 s, threshold ±2 s, fast −3 to −6 s per 100 m).

Sweat rate & fuelling

Sweat loss from a weigh-in, taking 1 kg of body mass as 1 litre of sweat:

sweat loss = weight before − weight after + fluid drunk − urine

The American College of Sports Medicine's position stand recommends personalised drinking to avoid losing more than about 2% of body weight from dehydration, without drinking more than you sweat (ACSM 2007). Our choice: the suggested range runs from the minimum that keeps you under 2% over your race time up to your sweat rate.

Carbohydrate per hour follows Jeukendrup's recommendations by duration (Jeukendrup 2014):

Our choices: the exact band edges (75 min, 2 h, 2.5 h) and the lower ends of each range. Gel counts use the carbs per gel you enter (25 g by default). General guidance for healthy adults, not medical advice.

Race fuelling plan (in the race-day planner)

• The carb target per hour comes from your whole race time (bands above); you can pick a number within it. Nothing during the swim.
• Fluid per hour: from your sweat rate if you know it (staying under 2% loss, never above your sweat rate), otherwise the ACSM starting range of 0.4–0.8 L per hour, aiming at the middle.
• Carbs in your drink mix count first; gels make up the rest.
• Coaching tips, not research: start eating about 15 minutes into the bike (10 into the run), stop about 10 minutes before the end of a leg, move gels off climbs steeper than 4% to just before them, and on the run take gels at aid stations with water.
• Bottles to start with = fluid needed until the first aid station, up to your number of bottle cages.
• Times and kilometres come from your terrain-adjusted splits.

Heart rate zones

With max and resting heart rate, zones use the heart rate reserve method (Karvonen et al. 1957):

target HR = resting HR + share × (max HR − resting HR)

If you leave max HR empty, it's estimated from age as 208 − 0.7 × age (Tanaka et al. 2001), a regression on thousands of adults. Individual values scatter by about ±10 bpm around it, so a measured max is better.

Coaching practice, not research: the five zones of 50–60%, 60–70%, 70–80%, 80–90% and 90–100% of heart rate reserve, and the threshold-based zones, which use Joe Friel's percentages of lactate threshold heart rate (separate for running and cycling) and his 30-minute test (Friel (coaching guide)).

Carb loading

Targets follow the joint position statement of the American College of Sports Medicine, the Academy of Nutrition and Dietetics and Dietitians of Canada (Thomas et al. 2016):

Our choices: daily totals are rounded to 10 g; "per meal" divides the day by five meals and snacks; the breakfast amount uses about 1 g per kg for each hour before the start (a common way to pick a point in the range, not a research rule). The "Build your day" foods use rounded, typical carbohydrate values from USDA FoodData Central; brands differ. The sample day is our own mix of mostly low-fibre foods, scaled to the middle of your range. The shopping list converts cooked rice and pasta to dry weight (about 0.35 and 0.41 g dry per g cooked).

Sources

• Riegel, P. S. (1981). Athletic Records and Human Endurance. American Scientist, 69(3), 285–290. Link
• Abbiss, C. R., & Laursen, P. B. (2008). Describing and understanding pacing strategies during athletic competition. Sports Medicine, 38(3), 239–252. Link
• Minetti, A. E., Moia, C., Roi, G. S., Susta, D., & Ferretti, G. (2002). Energy cost of walking and running at extreme uphill and downhill slopes. Journal of Applied Physiology, 93, 1039–1046. Link
• Martin, J. C., Milliken, D. L., Cobb, J. E., McFadden, K. L., & Coggan, A. R. (1998). Validation of a mathematical model for road cycling power. Journal of Applied Biomechanics, 14(3), 276–291. Link
• Swain, D. P. (1997). A model for optimizing cycling performance by varying power on hills and in wind. Medicine and Science in Sports and Exercise, 29(8), 1104–1108. Link
• Sinnott, R. W. (1984). Virtues of the Haversine. Sky & Telescope, 68(2), 159. Explainer
• Wakayoshi, K., Yoshida, T., Udo, M., Kasai, T., Moritani, T., Mutoh, T., & Miyashita, M. (1992). A simple method for determining critical speed as swimming fatigue threshold in competitive swimming. International Journal of Sports Medicine, 13(5), 367–371. Link
• Jeukendrup, A. E. (2014). A step towards personalized sports nutrition: carbohydrate intake during exercise. Sports Medicine, 44(Suppl 1), S25–S33. Link
• American College of Sports Medicine; Sawka, M. N., Burke, L. M., Eichner, E. R., Maughan, R. J., Montain, S. J., & Stachenfeld, N. S. (2007). Exercise and fluid replacement (position stand). Medicine & Science in Sports & Exercise, 39(2), 377–390. Link
• Tanaka, H., Monahan, K. D., & Seals, D. R. (2001). Age-predicted maximal heart rate revisited. Journal of the American College of Cardiology, 37(1), 153–156. Link
• Karvonen, M. J., Kentala, E., & Mustala, O. (1957). The effects of training on heart rate; a longitudinal study. Annales Medicinae Experimentalis et Biologiae Fenniae, 35(3), 307–315. Link
• Friel, J. Joe Friel's Quick Guide to Setting Zones. TrainingPeaks. Coaching practice, not a research study. Link
• Thomas, D. T., Erdman, K. A., & Burke, L. M. (2016). American College of Sports Medicine joint position statement: Nutrition and athletic performance. Medicine & Science in Sports & Exercise, 48(3), 543–568. Link
• U.S. Department of Agriculture, Agricultural Research Service. FoodData Central (carbohydrate values for common foods, rounded). Link