Most running apps compete on features. More metrics, more graphs, more data points, more things to track. The assumption is that more information makes you a better runner.
It doesn’t. More information makes you a more distracted runner. And distraction is the enemy of consistency.
Pacewright deliberately ignores several things that other apps track. Each omission has a specific reason.
Wind
Pacewright adjusts for heat, humidity, and altitude. It does not adjust for wind.
Why not? Because wind is genuinely hard to do well. Unlike temperature and dew point — which are consistent across a region and measured reliably — wind speed and direction change moment to moment and vary with terrain, buildings, trees, and which direction you’re running. A headwind on the way out becomes a tailwind on the way back. A calm start can turn gusty mid-run.
A bad wind adjustment — one that tells you to run slower when the wind isn’t actually affecting you, or doesn’t adjust when it is — is worse than no adjustment at all. We’d rather tell you to use RPE on windy days than give you a number that’s probably wrong.
Cadence
Your watch tracks your steps per minute. Pacewright doesn’t use it.
The “optimal cadence is 180 steps per minute” advice has been repeated so often that it sounds like settled science. It isn’t. That number came from Jack Daniels observing Olympic-level runners at the 1984 Games. It describes what fast runners do at fast paces — it doesn’t prescribe what slower runners should do at slower paces.
Cadence varies naturally with pace, height, leg length, and running experience. Artificially increasing your cadence to hit 180 often creates an awkward, choppy stride that wastes energy. Your cadence will naturally increase as you get faster and more efficient. There’s nothing for the algorithm to do with it.
Composite Wellness Scores (Body Battery, Recovery Advisor)
Your Garmin or Apple Watch might give you a “body battery,” “recovery advisor,” composite stress score, or composite sleep score. Pacewright ignores those specific composite outputs.
The reason isn’t that sleep and stress don’t affect running — they absolutely do. It’s that these scores roll multiple inputs (HRV, RHR, sleep duration, sleep stages, activity) into a single opaque number with proprietary weighting. The conversion has never been validated against running performance in published research. Your watch might say “poor recovery” when you feel great or “fully recovered” when you’re wiped, and you can’t audit why — so you can’t trust it.
The underlying signals are a different matter. HRV trend, RHR trend, and sleep duration are each individually well-supported in the recovery literature when interpreted as trends against your own baseline. Pacewright reads those directly from Garmin and uses them sparingly — there’s a full article on the specific thresholds. RPE is still the primary input either way. The line is between “raw signal compared to your baseline” (kept) and “proprietary composite told to you as a number” (ignored).
Machine Learning Predictions
Pacewright uses mathematical models with published formulas — Riegel, VDOT, Critical Speed. It does not use neural networks, AI models, or any form of machine learning.
This is the core design philosophy, not a technical limitation. Machine learning models are black boxes. They produce predictions that may be accurate but cannot be explained. “The model says you’ll run 51:30” doesn’t tell you anything useful. “The Riegel formula says 51:30 because your 5K time implies a fatigue factor of 1.06, which projects to this 10K time” tells you everything.
Transparency requires explainability. Explainability requires models you can show your work on. Down the road, the engine may tune itself to your individual response over time, but any such adaptation would stay inspectable, never a black box. That’s the only kind of learning we’d add.
Pace Data From Group Runs
When you run with a group or a partner, Pacewright counts the training load (duration × RPE) and the consistency (you showed up). It does not use the pace data for fitness trend analysis.
Why? Because your pace during a group run reflects the group’s pace, not your fitness. If you ran 9:00/mile because that’s what your running partner does, that number shouldn’t influence your predicted race time or your aerobic trend analysis. It’s someone else’s signal.
The “10% Rule”
Pacewright deliberately ignores the universal “never increase more than 10% per week” advice. Not because load management doesn’t matter — single-session limits, weekly volume limits, and what you report after a run are the foundation of the entire system — but because 10% is the wrong number for most runners.
Ten percent of 10 miles is a single mile — a trivially small step for a beginner whose body adapts quickly at that load. Ten percent of 60 miles is six, an entire extra session’s worth of stress landing on a runner who is already absorbing a lot every week. Same rule, opposite meaning. A universal 10% is too conservative for beginners and too aggressive for experienced runners, so Pacewright scales the allowed increase to the mileage you’re actually at: the more you run, the smaller the share you can add.
Weekly mileage is also only half the question. A week can sit comfortably inside its cap and still contain one run far longer than anything you’ve done in a month, which carries its own risk. In the largest study of runners to date, covering 5,205 runners and 588,071 recorded sessions, a session exceeding the runner’s longest run of the previous 30 days by more than 10% was associated with overuse injury.1 So Pacewright caps the week and caps the single run, separately.
”What If” Scenarios
There is no “what if I ran 50 miles this week?” simulator. Running a hypothetical scenario requires calibrating how your body would respond to a training load you haven’t done — which is speculation, not prediction. We’d rather not show you a number we can’t defend.
Apple HealthKit and Google Fit
Pacewright integrates with Strava and Garmin. It does not integrate with Apple HealthKit or Google Fit.
HealthKit requires a native iOS app. Pacewright is a web app — it runs in your browser, on any device, without installation. Building a native app solely for HealthKit integration would mean maintaining a separate codebase for a single data source.
Google Fit stopped accepting new integrations. It’s a dead platform.
The Philosophy
Every feature in a training app has a cost. Not just the engineering cost — the cognitive cost to the user. One more number on the screen is one more thing to worry about, one more thing to optimize, one more thing that can make you feel like you’re doing it wrong.
Pacewright’s approach: include what the science supports, explain how it works, and leave out everything else. If a metric doesn’t change what you should do on your next run, you don’t need to see it.