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How to use DataFrame.fit. Search below, or browse by topic.
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Getting started
Sync and connections
- Connect Garmin ConnectHow to link Garmin Connect to DataFrame.fit in Settings. Garmin is the recommended watch and wellness source. Polar is also supported as an alternative primary watch. WHOOP can sit alongside Garmin.
- Connect PolarHow to link Polar Flow to DataFrame.fit in Settings. Polar is supported as a primary watch alongside Garmin. Connect one watch at a time.
- Connect WHOOPHow to link WHOOP to DataFrame.fit in Settings. Import workouts, sleep, recovery and strain. WHOOP can sit alongside Garmin. There is no plan push to WHOOP.
- Add sessions to Google CalendarHow optional Google Calendar sync works in DataFrame.fit. On Calendar, connect Google Calendar to write upcoming planned sessions, races, and logged activities to a DataFrame.fit calendar on the Google account you signed in with.
- Sync your trainingHow Sync works in DataFrame.fit. Pull Garmin activities and wellness into one dashboard. The first sync can take a few minutes. New sessions can appear on Home before Sync fully finishes.
- Connect TrainingPeaks and MyWhooshHow optional TrainingPeaks and MyWhoosh connections work in DataFrame.fit. Garmin stays the primary log. TrainingPeaks is for coach plans and sessions that never reached Garmin. MyWhoosh is for indoor rides captured there.
Training plan
- Plan the week onto your GarminHow to add workouts on Calendar in DataFrame.fit and send structured sessions to Garmin. Plan yourself, paste an AI week, or pull a Google Sheet, Garmin Coach, or TrainingPeaks calendar on Training Plan.
- Connect a coach Google SheetHow to pull a coach Google Sheet into DataFrame.fit. Paste the Share link, set General access to Anyone with the link, pick the tab, and map Date and workout columns.
- Coach athletes on DataFrame.fitHow the free DataFrame.fit coach portal works: become a coach, invite athletes, see who needs a look, read recovery against each athlete's own range, and assign templates and blocks to Calendar and the watch.
Activities and quality
- Compare quality blocksHow quality-block compare works in DataFrame.fit. Compare the hard intervals across sessions the way coaches talk, not only full-session averages. Open Session Quality or add activities to compare.
- Compare weeksHow week compare works in DataFrame.fit. Put two to four Monday-Sunday weeks side by side - training load, heart rate, sleep, HRV, Form, weather, and the sessions in each week. Open it from Calendar or a race.
- Brick sessions and fadeHow DataFrame.fit detects same-day paired sessions (bike-run, strength-run, hybrid) and labels fade on the second leg. Open Bricks to see history, or check the second activity after a brick day.
- HYROX in DataFrameHow DataFrame.fit treats HYROX and CrossFit as first-class sports on Garmin data: tagging, volume splits, brick pairs, muscle-map relevance, and race formats.
- Races and personal bestsHow races work in DataFrame.fit. Add A, B, or C races, mark a Garmin session as a race, and read personal bests by format on Analysis. Close A and B races also shape Home in race week.
Recovery
- Use today's plan checkHow today's plan works on Home in DataFrame.fit. See today's session, how form and fitness may change if you complete it, and whether overnight recovery still fits the work.
- Read RecoveryHow the Recovery page works in DataFrame.fit. See sleep, HRV, Body Battery, and readiness from Garmin, compared with your recent baseline - then decide whether today's work still fits.
- Fitness and FormHow Fitness and Form works in DataFrame.fit. Form is freshness (fitness minus recent fatigue), shown in words on Home and as a chart on Fitness and Form. VO2, lactate threshold, and cycling FTP trends appear when Garmin has them.
- Garmin metrics in plain languageA cheat sheet for Garmin training status, readiness, Body Battery, VO2 max, and Training Effect - what the words mean, and where DataFrame.fit shows them next to your plan.
Nutrition
Sharing
Settings
- Connect an AI assistant to DataFrameConnect Claude from the Claude directory, ChatGPT with Developer mode, Cursor with one click, or another assistant with the DataFrame MCP URL - including GitHub Copilot, Codex, Gemini, Grok, and DeepSeek. Sign in on DataFrame and choose what each one may view or change.
- Connect ChatGPT to DataFrameTurn on ChatGPT Developer mode, create an MCP app pointed at https://dataframe.fit/api/mcp, sign in on DataFrame, choose permissions, then ask about your training from a normal chat.
- What an AI agent can do on DataFramePermissions for the DataFrame MCP: activities, plan, nutrition, wellness, races, and push to Garmin.
- Simple or Detailed dashboardHow Simple and Detailed display density works in DataFrame.fit. Simple shows big rounded icons and the main number. Detailed keeps labels, trends, and targets. Phones start in Simple.
- Pick the sports you trainHow Your sports works in DataFrame.fit. Mark every sport you train and choose a primary so Home, volume, bricks, tips, and race formats stay relevant - nothing is buried as other.
- Training zones and FTPHow to set heart-rate zones, cycling FTP, and W prime in DataFrame.fit. Sync can import Garmin cycling FTP. Outdoor run pace per HR zone comes from recent outdoor runs, not treadmill tests.
- Move your TrainingPeaks libraryFor coaches: how to bring your TrainingPeaks workout library into DataFrame.fit with an export file you make yourself, what to do if something goes wrong, and why the export button is optional and your choice.
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