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Plain-English guide · No jargon

Data Dictionary

Every chart, metric and model in this dashboard explained in everyday language. If a term ever feels unclear, look it up here.

How to read confidence levels

ConfidenceWhat it meansHow to act on it
HighStrong evidenceTrustworthy. Good for planning and acting on.
MediumUseful guideTake it as a directional hint, not a verdict.
LowEarly signalTreat as a hypothesis worth verifying.

Dataset reconciliation (audit)

Every Executive Overview KPI has been reconciled against the source export activities_1225.xlsx. The numbers below are the frozen ground-truth used by the in-app integrity checker.

KPIGround truthDefinition
Activities1,925Row count from the Strava export.
Total distance52,699 kmΣ distance ÷ 1,000.
Total elapsed time3,051.75 hrsΣ elapsed_time ÷ 3,600.
Avg distance / activity27.4 kmTotal distance ÷ activities.
HR-tracked activities1,783Activities where avg HR > 0.
Avg HR138 bpmMean of avg HR across HR-tracked activities.
Max HR observed211 bpmSingle highest avg HR in dataset.
Active ISO weeks467DISTINCTCOUNT of ISO-8601 year+week (Mon-start, week 1 contains Jan 4).
Avg activities / month15.9Activities ÷ calendar months in active window (≠ active months).

Date parsing

Strava CSV dates are parsed exactly as %b %d, %Y, %I:%M:%S %p in UTC, then truncated to a YYYY-MM-DD day key.

ISO week rule

ISO-8601: Monday is day 1; week 1 of any year is the week containing 4 January. Years can have 52 or 53 weeks — never capped.

CTL · ATL · TSB

CTL = 42-day exponentially-weighted load (λ = 1/42). ATL = 7-day EWMA. TSB = CTL − ATL. Load proxy = elapsed minutes × intensity factor.

ACWR (injury proxy)

Acute (7d km) ÷ Chronic (28d km ÷ 4). Flagged > 1.5 (overload) or < 0.8 (under-load). Capped to avoid divide-by-zero on returning weeks.

Core Metrics

Distance

High
What it is
Total kilometres covered in a workout.
How it's worked out
Comes straight from your GPS-recorded activity.
How to read it
More kilometres = more volume. Stack lots of weeks of distance to build endurance.

Moving Time vs Elapsed Time

High
What it is
How long you were actually moving vs total time the watch was running.
How it's worked out
Moving time pauses when you stop; elapsed time does not.
How to read it
Big gap = lots of stops (lights, café, photos). Use moving time to compare effort fairly.

Average & Max Heart Rate

High
What it is
Your typical and peak heart rate during a workout.
How it's worked out
Recorded by your chest strap or watch every few seconds, then averaged.
How to read it
Higher avg HR = harder effort. Max HR rarely sustained for long.

Heart Rate Zones (Z1–Z5)

High
What it is
Five effort levels based on a percentage of your maximum heart rate.
How it's worked out
Z1 < 60% · Z2 60–70% · Z3 70–80% · Z4 80–90% · Z5 ≥ 90% of estimated Max HR.
How to read it
Z1–Z2 builds endurance. Z4–Z5 builds speed. Spending most time in Z3 (the 'grey zone') is usually inefficient.

Predicted Max HR (Tanaka formula)

High
What it is
An age-based estimate of the highest your heart can beat.
How it's worked out
208 − (0.7 × your age). For example, age 39 → 181 bpm.
How to read it
It's a rough guide for setting zones. Your actual max can be ±10–15 bpm different.

Personal Record (PR)

High
What it is
Your best-ever time or pace for a given distance or sport.
How it's worked out
Tracked across all your activities for each common distance (5 km, 10 km, etc.).
How to read it
PRs cluster when you're peaking. Long PR droughts can mean fatigue or under-training.

Volume & Activity

Monthly Training Volume

High
What it is
How many activities and kilometres you logged each month.
How it's worked out
We bucket every recorded activity by calendar month and sum the count and distance.
How to read it
Look for seasonal build-ups (spring/summer peaks) and recovery dips. Consistent month-on-month volume is a strong base.

Active Weeks per Year

High
What it is
Number of calendar weeks each year where you logged at least one workout.
How it's worked out
Out of 52 possible weeks, we count the ones with ≥1 activity.
How to read it
40+ active weeks signals a strong, sustained habit. Big drops can flag injury, burnout or life events.

Longest Streak

High
What it is
The most consecutive days in a row that you trained.
How it's worked out
We scan your daily activity log and find the longest unbroken run of training days.
How to read it
Streaks are motivating but not always healthy — rest days matter for adaptation.

Sport Mix / Activity Mix

High
What it is
The share of your training time or distance that comes from each sport.
How it's worked out
We group activities by sport (Ride, Run, Swim, Other) and divide each by the total.
How to read it
A balanced mix reduces injury risk; a heavy single-sport mix shows specialisation.

Season Drop-off

High
What it is
How much your training volume falls after the main season ends.
How it's worked out
We compare distance covered Jan–Oct against Nov–Dec each year.
How to read it
A big drop is a normal off-season taper. A small drop suggests year-round consistency.

Time-of-Day Pattern

High
What it is
When during the day you typically train.
How it's worked out
Each activity's start time is bucketed into Early Morning, Morning, Afternoon, Evening or Night.
How to read it
Reveals your training rhythm — useful for spotting routines or scheduling conflicts.

Day-of-Week Pattern

High
What it is
Which weekdays you train most often.
How it's worked out
We count activities by the day of the week they happened on.
How to read it
Highlights your weekly rhythm — e.g. weekend long rides, midweek runs.

Performance Detail

HR Histogram (Time in Zone)

High
What it is
How many activities fall into each 10-bpm heart-rate bucket, coloured by training zone.
How it's worked out
We round each activity's average HR to the nearest 10 bpm and colour it by Z1–Z5 against your age-predicted max.
How to read it
A wide spread = varied intensity. A spike in Z3 is the 'grey zone' to avoid.

HR Box Plot by Sport

High
What it is
How variable your effort is in each sport.
How it's worked out
For each sport, the box covers the middle 50% of efforts (Q1–Q3); whiskers show min/max; line in the middle is the median.
How to read it
Wider boxes = more variable intensity. Narrow boxes = very consistent effort.

HR vs Duration Scatter

High
What it is
Each dot is one workout — duration on the X-axis, average HR on the Y-axis.
How it's worked out
Plotted directly from your activity log, coloured by sport.
How to read it
Top-right dots = long efforts at high intensity (impressive but taxing). Bottom-left = easy short sessions.

Elevation Climbed

High
What it is
Total vertical metres gained across all your activities.
How it's worked out
Summed from each activity's GPS elevation gain.
How to read it
Hilly sessions add stress beyond what distance alone shows. Big climbing weeks deserve extra recovery.

Calories Burned

Medium
What it is
Estimated energy expenditure across your training.
How it's worked out
Strava's estimate based on duration, HR, sport and (if available) power.
How to read it
Useful as a rough guide for fuelling — not precise enough for strict diet tracking.

Training Load

Training Load (TRIMP)

High
What it is
A single number that captures how hard a workout was.
How it's worked out
Combines duration with average heart rate — long + hard sessions score the highest.
How to read it
Higher score = more stress on the body. Use it to plan recovery days.

CTL — Fitness

High
What it is
Your long-term fitness, built up slowly.
How it's worked out
A 28-day rolling average of daily training load.
How to read it
Higher CTL = fitter. It rises slowly with consistent training and falls with rest.

ATL — Fatigue

High
What it is
Your short-term tiredness from recent workouts.
How it's worked out
A 7-day rolling average of daily training load.
How to read it
ATL spikes after hard weeks. Give it time to drop before key efforts.

TSB — Form

High
What it is
How fresh you feel right now.
How it's worked out
Fitness − Fatigue (CTL − ATL).
How to read it
Positive TSB = fresh & race-ready. Negative TSB = tired but building. Strongly negative = at risk of overtraining.

AI Insights

Changepoint Detection

High
What it is
Finds the moments when your training habits shifted significantly.
How it's worked out
Scans your weekly distance history and flags weeks where the average level jumped or dropped.
How to read it
Changepoints often line up with life events (new job, new sport, injury comeback).

Era Clustering

High
What it is
Groups your training years into 'chapters' that look similar.
How it's worked out
Compares each year by volume, intensity and sport-mix, then clusters years that resemble each other.
How to read it
Useful for telling the story of your athletic career — e.g. 'cycling era' vs 'multi-sport era'.

Trend & Seasonality (STL)

High
What it is
Splits your training history into the long-term trend, the yearly cycle, and the noise.
How it's worked out
A statistical recipe (STL) separates a monthly time series into three clean layers.
How to read it
The trend tells you if you're building, the seasonal layer shows your annual rhythm.

Anomaly Detection

High
What it is
Spots workouts that look unusually different from your normal pattern.
How it's worked out
Compares each session to your last 28 days. If pace, HR, distance or elevation are way off the average, it's flagged.
How to read it
Anomalies are often races, breakthroughs, or bad days — worth a quick look.

HR Age Benchmarking

Medium
What it is
Compares your observed peak heart rate to the age-predicted Tanaka norm.
How it's worked out
A linear regression on your monthly max-HR series is plotted against the Tanaka band (208 − 0.7·age, ±5 bpm). The slope shows year-over-year drift; the gap shows where you sit vs the population.
How to read it
Above-band peaks suggest a genetically high ceiling; below-band peaks plus a steep negative slope can hint at fatigue, heat or detraining.

Top Discoveries (auto-surfaced)

Medium
What it is
The three most newsworthy findings the engine pulls from the patterns above.
How it's worked out
Each model emits a candidate insight with a tone and confidence; the engine ranks them and surfaces the top three at the page header.
How to read it
Use them as a quick read of what changed — every card links to the detailed model below.

Environment & Gear

Optimal Temperature

Medium
What it is
The temperature range where you tend to perform best.
How it's worked out
We fit a curve through your pace vs. recorded temperature data and pick the peak.
How to read it
Most endurance athletes peak between 8–15°C. Hot/cold sessions cost a few % of pace.

Current Conditions Score

Medium
What it is
A 0–100 score for how favourable today's weather is for training.
How it's worked out
Compares current temperature and humidity against your personal optimum.
How to read it
80+ = ideal, 50–80 = workable, below 50 = expect slower paces or higher HR for the same effort.

Activity Detail

Activity Drill-through Table

High
What it is
The raw, row-by-row record of every workout in the current filter.
How it's worked out
Each row is one Strava activity with sortable columns (date, time-of-day, sport, name, distance, elapsed/moving time, avg & max HR). The current filter set can be exported as CSV.
How to read it
Use it to drill into a specific session, sort by any metric, search by name, or export a filtered CSV for offline analysis.

Year in Review

Peak Year / Peak Month

High
What it is
Your single highest-volume year and month.
How it's worked out
We rank every year (and every month) by total distance and pick the top one.
How to read it
Useful as a personal benchmark — the bar to beat.

Year-over-Year (YoY) Distance

High
What it is
How this year's distance compares to last year's at the same point.
How it's worked out
We compare cumulative distance to date against the equivalent period in the prior year.
How to read it
Positive % = ahead of last year. Negative = behind. Useful for staying honest.

Personal Records of the Year

High
What it is
Your single longest, fastest and biggest-climbing session of the selected year.
How it's worked out
Within the year filter we pick the activity with the maximum distance, max average speed and max elevation gain respectively.
How to read it
A quick highlight reel — the three sessions worth remembering from that year.

Active Days & Longest Streak

High
What it is
How many calendar days you trained in the year, and the longest unbroken run of training days.
How it's worked out
We count distinct activity dates within the year and scan for the longest consecutive sequence.
How to read it
More active days = stronger habit; long streaks are motivating but rest days still matter for adaptation.

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Training Evolution

Athlete Intelligence · v1.0

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