Fysiqal
Tracking
Tracking

Building a Simple Dashboard

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DefinitionA short reference note, not a full lesson.
Definition

A good dashboard shows a few goal-relevant metrics as smoothed trends — leading indicators for action, lagging indicators for confirmation — and hides the rest.

Detail

A dashboard turns the data layer into decisions. The design principles:

  • Show few metrics, chosen by goal. Surface only the KPIs that matter for the user's current goal (see KPIs for Fat Loss, KPIs for Strength, KPIs for Endurance). A wall of numbers causes paralysis and over-tracking (see Avoiding Over-Tracking and Obsession).
  • Pair leading and lagging. Put leading indicators (adherence streaks, sessions done, weekly volume, steps) up top for daily action, and lagging outcomes (weight trend, e1RM, FTP, PRs) below for the long-arc story (see Leading vs Lagging Indicators).
  • Plot smoothed trends, not raw points. Use moving-average lines (e.g. 7-day trend weight) so the eye reads signal, not noise. Show the raw points faintly if at all.
  • Anchor to goals. Overlay the target rate / goal line so "on track vs off track" is visible at a glance — this connects to SMART goals.
  • Right cadence per tile. Daily tiles (weight trend, readiness, steps), weekly tiles (volume, adherence, active minutes), and per-block tiles (re-test results) per How Often to Measure.
  • Celebrate wins. Auto-surface recent PRs and streaks — they drive adherence.

A minimal viable dashboard for most users: trend weight with goal line, this week's adherence (sessions + nutrition), a goal-specific output trend (e1RM / pace-at-HR / waist), and a recent-PR / streak banner. Build with privacy defaults in mind (see Health-Data Privacy Basics).

Key facts

  • Show few, goal-relevant metrics; hide the rest to avoid paralysis.
  • Pair leading indicators (action) with lagging outcomes (confirmation).
  • Plot smoothed moving-average trend lines, not raw daily points.
  • Overlay the goal/target line so on-track status is glanceable.
  • Use per-metric cadence (daily/weekly/per-block) and surface PRs/streaks.

Connections

Sources

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Established dashboard/KPI design practice applied to fitness data.

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Atlas Connections

Health-Data Privacy Basics
Fitness and health data is sensitive and often not covered by medical-privacy laws — know who can see it, where it's stored, and what you're consenting to share.
KPIs for Endurance
Track weekly training volume and intensity distribution as the inputs, and pace-at-HR / FTP / efficiency as the outputs that confirm aerobic fitness is rising.
KPIs for Fat Loss
Track the bodyweight trend + waist + photos to confirm fat is leaving, and nutrition adherence + step floor as the controllable inputs driving it.
KPIs for Strength
The headline strength KPI is the estimated-1RM trend on your main lifts; behind it, track that load is progressing at controlled effort (RPE/RIR) over the block.
Leading vs Lagging Indicators
Leading indicators are the controllable behaviors that predict results (workouts done, nutrition adherence); lagging indicators are the slow outcomes they produce (weight, strength, FTP).
How Often to Measure
Match measurement frequency to how fast each metric actually changes — daily for noisy fast signals you'll average, weekly to monthly for slow ones, periodically for fitness re-tests.
Moving Averages
A moving average replaces each noisy daily reading with the average of a recent window, turning a jagged metric into a readable trend line.
Avoiding Over-Tracking and Obsession
Tracking should serve your training and well-being, not rule them — when the data causes anxiety, distorts behavior, or becomes the goal itself, measure less.
Goal-Setting with Metrics (SMART)
Turn vague aims into SMART goals — Specific, Measurable, Achievable, Relevant, Time-bound — and pair each outcome goal with the process goals you actually control.