Skip to content
Striiive
Request early access

Science & Research

The thinking
behind your
progress.

A lifelong story.
A clearer way to understand it.

Every athlete’s development tells a different story. Striiive brings together records over time, relevant benchmarks, and clear information about data sources to help athletes, parents, and coaches understand that story.

Take the long view
A symbolic sequence of the same runner at four stages of life: a child, a teenage junior athlete, a young adult, and an adult, moving forward along one continuous track.
One athlete. Many chapters. A symbolic illustration of the journey from childhood through adulthood.

01 / Progress takes time

A season is a chapter.
Keep the whole story.

A single session captures one moment. An athletic history lets you follow the changes across months, seasons, and years.

Striiive keeps that history connected as sports, coaches, and devices change. The aim is to give each new chapter the context of the work that came before it.

02 / Numbers need context

A point of reference.
Room for your own path.

Where an applicable reference is available, Striiive compares recorded metrics with reference bands for age and sex to estimate a percentile.

That position helps put a number in context. It describes a comparison with a reference group; it does not predict an athlete’s future performance or potential.

A reference comparison and your own progress over time offer different perspectives. Both need context.

03 / The source matters

Know what’s
behind a reading.

Records retain information about where they came from, including device imports and manual entries. Passport summaries make those contributing sources visible.

Import checks screen readings against supported ranges and identify repeated records, helping keep an athlete’s history consistent.

Source information and import checks help explain a record. They do not certify a device’s measurement accuracy.

04 / More of the story

A clearer picture starts
with knowing what’s there.

Recent data coverage tells you how much information is available to work with. Gaps in recording are part of that context, too.

Striiive’s current benchmark coverage indicator counts days with data in a 30-day window and reaches its maximum at 14 recorded days.

This indicator describes data availability. It is separate from measurement accuracy and statistical confidence.

Benchmark data coverage
30day window
14recorded days to reach
the indicator’s maximum

Current calculation, explained. This is a description of the method, not a live athlete record.

05 / Understand the calculation

A score should come
with an explanation.

Readiness is a calculated indicator built from available heart-rate variability, sleep duration, resting heart rate, and exercise minutes.

The current method converts these inputs to a common scale, combines them using the weights shown here, and rounds the result to a score from 0 to 100.

  • When an input is missing, the available inputs are reweighted proportionally.
  • When there are no available readings, readiness is marked as unknown.

A calculated score is a way to summarize the available inputs. A recorded measurement is the underlying reading.

What goes into readiness

Default weights when all four inputs are available.

  • Heart-rate variability40%
  • Sleep duration25%
  • Resting heart rate20%
  • Exercise minutes15%

These are the current product’s calculation weights. They describe how the indicator is assembled.

Further reading

Research behind
the wider context.

These publications explain why age, recording conditions, and device accuracy matter when interpreting fitness readings. They provide background reading; they do not validate Striiive’s readiness weights or establish the source of every reference band used in the product.

  1. Fleming et al. (2011). Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age.

    A systematic review of observational studies, published in The Lancet.

  2. Shaffer & Ginsberg (2017). An Overview of Heart Rate Variability Metrics and Norms.

    A review of HRV metrics and measurement context in Frontiers in Public Health.

  3. Shcherbina et al. (2017). Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort.

    A device validation study in the Journal of Personalized Medicine.

Keep asking good questions

Your story deserves
clear explanations.

Have a question about a metric, a comparison, or the way a score is calculated? We’d like to hear it.

Talk to the team Our approach to data integrity
Athlete Development Science & Fitness Metrics | Striiive