How it works

The maths behind the prediction, in plain words.

Then vs now

Pick a past race or time trial. Splitcast looks at the 42 days before it (race day itself left out) and at your last 42 days, and works out the same markers for both windows. The difference between them is how much fitter, or less fit, you are now.

Health doesn't mark which runs were races, so you choose them. Splitcast suggests your fastest runs at 5k, 10k, half and marathon distance, and you can add races that aren't in Health and correct times to chip times.

The markers

Four markers measure your aerobic engine. They feed the prediction:

MarkerWhat it measuresNeeds
VO2maxApple Watch's estimate of your aerobic capacityA Watch reading in the 3 months before
Distance per heartbeatHow far you travel for each beat on steady outdoor runs, with climbing counted as extra distance3+ steady outdoor runs with heart rate
Power per heartbeatRunning power for each beat on the same steady runs3+ steady runs with Watch running power
Critical powerFrom your hardest 3- and 12-minute effortsWatch running power

Others give context but don't change the time: training load (fitness), form (fitness minus fatigue), resting heart rate, HRV and sleep.

Missing data is never counted as zero. A marker without enough data is left out and the app says why. If you think a marker's data is wrong, you can turn it off in Results › Prediction markers.

The prediction

Your time then is scaled by how much the markers have changed. If they're 4% better than before your race, your time is predicted about 2% faster, because the time is scaled by the square root of the change:

time now = time then ÷ √(average marker now ÷ average marker then)

The likely range shows the most and least hopeful single marker. With no races added yet, your fastest mile in the last 8 weeks stands in as a rough starting point, and the app says so.

Other distances

To predict a different distance, Splitcast uses Riegel's formula: time grows with distance to a power.

time₂ = time₁ × (distance₂ ÷ distance₁)k

The textbook power is 1.06, which assumes you're trained for the distance. Most runners slow down more than that over long races, so when you have results at two distances within a year, Splitcast works out your own power from them.

One runner's 5k time predicted a 3:19 marathon with the textbook power. Their real marathons were 3:56 and 4:14. Their own power (1.14) predicted 3:54. Add a few races at different distances for the best predictions.

How good is it?

On the Goal tab, "How good is this?" shows what the app would have predicted for each of your past races, using only data from before them. It's the honest test: if it's often far off for you, treat predictions as a rough guide.

Across real race results while it was being built, adding hills and critical power took the average error from 3.8% to 3.2%, about 40 seconds on a 20-minute 5k.

Limits