fitops analytics

Training analytics computed from your local activity database.

All analytics commands require synced activities. Run fitops sync run first.

Output is human-readable by default. Add --json to any command for raw JSON output.

Commands

fitops analytics training-load

Show CTL (fitness), ATL (fatigue), and TSB (form) over time.

fitops analytics training-load [OPTIONS]

Options:

Flag	Default	Description
--days N	90	Days of history to return
--sport TYPE	all	Filter by sport type (e.g. Run, Ride)
--today	false	Return only today's current values (no history array)
--json	false	Output raw JSON instead of the formatted summary

Examples:

fitops analytics training-load
fitops analytics training-load --days 42 --sport Run
fitops analytics training-load --today

See Concepts → Training Load for how CTL/ATL/TSB are calculated.

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fitops analytics vo2max

Estimate VO2max from recent run activities.

fitops analytics vo2max [OPTIONS]

Options:

Flag	Default	Description
--activities N	50	Number of recent qualifying activities to consider
--age-adjusted	false	Apply an age-based decline factor to the estimate
--method METHOD	composite	Method to display: daniels, cooper, or composite
--save	false	Save the selected method's result as a manual override
--set-override VALUE	—	Directly set a VO2max override value (ml/kg/min)
--clear-override	false	Clear any previously saved manual override
--json	false	Output raw JSON instead of the formatted summary

Requires at least one run of 1500m or more. LTHR or max HR must be configured first (used to identify qualifying hard efforts). Uses a weighted composite of three formulas (VDOT 50%, McArdle 30%, Costill 20–40%).

fitops analytics vo2max
fitops analytics vo2max --activities 20
fitops analytics vo2max --age-adjusted

# Pin the VDOT estimate as your override
fitops analytics vo2max --method daniels --save

# Set override manually
fitops analytics vo2max --set-override 54.2

# Clear override and return to computed estimate
fitops analytics vo2max --clear-override

The --age-adjusted flag reads the athlete's birthday from the local database (synced from Strava) and applies a decline factor of 0.8% per year above age 25. The factor is floored at 0.5. See Concepts → VO2max for full methodology.

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fitops analytics zones

Calculate heart rate training zones from your physiology settings.

fitops analytics zones [OPTIONS]

Options:

Flag	Description
--method METHOD	Zone method: lthr, max-hr, hrr. Auto-selected if omitted.
--set-lthr BPM	Save your lactate threshold HR
--set-max-hr BPM	Save your maximum HR
--set-resting-hr BPM	Save your resting HR
--set-lt1 BPM	Manually override the LT1 (aerobic threshold) display value
--set-lt2 BPM	Manually override the LT2 (lactate threshold) display value
--clear-lt1	Clear LT1 override and return to computed value
--clear-lt2	Clear LT2 override and return to computed value
--infer	Infer LTHR, max HR, and pace thresholds from cached activity streams

First-time setup — set your values manually:

fitops analytics zones --set-lthr 165
fitops analytics zones --set-max-hr 192 --set-resting-hr 48

Or infer from your activity data:

fitops analytics zones --infer

The --infer flag analyses HR data from all activities with cached streams. It uses 20-minute rolling window averages to estimate LTHR (90th percentile of rolling averages), max HR (98th percentile), and resting HR (5th percentile). The result includes a confidence score (0–100) based on number of activities analysed, HR data quality, and consistency.

Inferred values are saved to ~/.fitops/athlete_settings.json with source tagged as "inferred". Zone display runs immediately after inference.

Then compute zones:

fitops analytics zones
fitops analytics zones --method lthr
fitops analytics zones --method hrr

Settings are stored in ~/.fitops/athlete_settings.json and reused across runs.

See Concepts → Zones for zone method details.

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fitops analytics trends

Analyse training trends: volume, consistency, seasonal patterns, and performance.

fitops analytics trends [OPTIONS]

Options:

Flag	Default	Description
--sport TYPE	all	Filter by sport type (e.g. Run, Ride)
--days N	180	Days of history to analyse

fitops analytics trends
fitops analytics trends --sport Run --days 365

Output includes:

• volume_trend — weekly distance with linear regression slope and direction (increasing / decreasing / stable)
• consistency — consistency score (0–1), weekly training frequency, average days between activities
• seasonal — per-season activity count, total distance, and average pace
• performance_trend — monthly pace and HR trends with improvement rate
• summary_label — plain-text summary (e.g. "volume building, consistent training, pace improving")

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fitops analytics performance

Show performance metrics derived from recent activities.

fitops analytics performance [OPTIONS]

Options:

Flag	Default	Description
--days N	365	Days of history to analyse
--sport TYPE	Run	Sport type: Run or Ride

fitops analytics performance --days 180
fitops analytics performance --sport Ride

Running metrics:

Field	Description
running_economy_ml_kg_km	Estimated oxygen cost per km (proxy from average pace)
pace_efficiency_score	0–100 score based on pace consistency across recent runs
variability_index	Coefficient of variation across pace values
aerobic_efficiency_trend	Early-vs-recent speed per heartbeat trend, including estimated HR change at the recent benchmark pace

Cycling metrics:

Field	Description
ftp_estimate_watts	95% of mean power from recent rides
power_to_weight_w_kg	FTP estimate / athlete body weight
normalized_power_ratio	Mean NP/AP ratio across recent rides
power_consistency	0–100 score based on power consistency
variability_index	Coefficient of variation across power values

Shared context:

Field	What it means
current_load	Current CTL / ATL / TSB snapshot used by the dashboard and CLI
trends	Training trend summary for the selected sport and time window

The dashboard performance page uses the same underlying data and adds a sport switch plus a profile link so you can compare current fitness, recent load, and threshold settings in one place.

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fitops analytics power-curve

Compute mean maximal power (MMP) curve and fit a critical power model.

fitops analytics power-curve [OPTIONS]

Options:

Flag	Default	Description
--sport TYPE	Ride	Sport type: Ride or Run
--activities N	20	Max number of recent activities with streams to use

fitops analytics power-curve
fitops analytics power-curve --sport Run --activities 10

Requires activities with cached streams (fitops activities streams <id> or bulk sync).

Output includes:

• mean_maximal_power — best average power/speed at standard durations (5s, 10s, ..., 7200s)
• critical_power_watts — CP from the two-parameter P = CP + W'/t model (cycling only, requires scipy)
• w_prime_joules — anaerobic work capacity in joules
• model_r_squared — goodness of fit for the CP model
• zones_from_cp — 6-zone power zones derived from CP
• power_to_weight — FTP estimate and W/kg (if athlete weight is stored)

If scipy is not installed, the CP model is skipped and only MMP values are returned.

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fitops analytics pace-zones

Show or configure running pace zones based on threshold pace.

fitops analytics pace-zones [OPTIONS]

Options:

Flag	Description
--set-threshold-pace MM:SS	Set your threshold pace per km (e.g. 5:00 or 4:45)

This command does not require authentication — it reads and writes local settings only.

# Set threshold pace
fitops analytics pace-zones --set-threshold-pace 5:00

# View current pace zones
fitops analytics pace-zones

5-zone structure (derived from threshold pace T):

Zone	Name	Range
1	Easy	> T × 1.16
2	Aerobic	T × 1.08 – T × 1.16
3	Tempo	T × 1.02 – T × 1.08
4	Threshold	T × 0.96 – T × 1.02
5	VO2max	< T × 0.96

Pace signal preference: when assigning laps or efforts to zones, FitOps uses the best available pace metric:

1. True Pace — GAP + weather normalised, if streams and weather data are available (most accurate on hilly or windy courses)
2. GAP (Grade-Adjusted Pace) — if streams are available but weather is missing
3. Raw pace — fallback if neither streams nor weather are available

This hierarchy also applies to LT2 inference: inferred threshold estimates are significantly more reliable when computed from True Pace rather than raw pace. See Concepts → Weather & Pace for details.

Threshold pace is stored in ~/.fitops/athlete_settings.json.

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fitops analytics recalculate-scores

Recompute cached aerobic score, anaerobic score, and training stress score (TSS) for all activities and persist them to the database.

fitops analytics recalculate-scores [OPTIONS]

Options:

Flag	Default	Description
--json	false	Output raw JSON instead of the formatted summary

fitops analytics recalculate-scores
fitops analytics recalculate-scores --json

Scores and TSS are derived from each activity's pace, HR, and current physiology settings (~/.fitops/athlete_settings.json). Run this command after updating LTHR, max HR, FTP, or threshold pace so historical activity rows and workout contribution analytics reflect your current settings.

JSON output:

{
  "_meta": { ... },
  "recalculated": 312
}

This command does not contact Strava — it only reads and writes the local database.

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fitops analytics snapshot

Compute and save today's analytics snapshot (CTL, ATL, TSB, VO2max) to the database.

fitops analytics snapshot

This command is useful for automation — run it daily via cron to build a historical record of your fitness metrics. It is idempotent per day, safe to run multiple times.

Snapshot saved  2026-04-06
  CTL     41.7
  ATL     54.0
  TSB     -12.3
  VO2max  55.4 ml/kg/min

Physiology Settings

Analytics that depend on HR-based calculations (zones, snapshot) read from ~/.fitops/athlete_settings.json. Set your values once with --set-* flags and they persist.

Setting	Flag	Used By
LTHR (lactate threshold HR)	--set-lthr	zones, snapshot
Max HR	--set-max-hr	zones
Resting HR	--set-resting-hr	zones (HRR method)
Threshold pace	--set-threshold-pace	pace-zones

See Also

• Concepts → Training Load
• Concepts → VO2max
• Concepts → Zones
• Output Examples → Analytics

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