Athlytics: A Reproducible Framework for Endurance Data Analysis

Tools for reproducible, offline analysis of endurance-training data exported from 'Strava'. Provides data import, quality-control, cohort-reference, and visualization helpers for sports-science indicators including acute:chronic workload ratio, aerobic efficiency, cardiovascular decoupling, exposure, and personal-best profiles.

Athlytics provides tools for reproducible, offline analysis of endurance training data exported from Strava. It includes data import, quality-control, cohort-reference, and visualization helpers for sports-science indicators.

Main Functions

Data Loading:

• load_local_activities(): Load activities from Strava export ZIP or directory

• parse_activity_file(): Parse individual FIT/TCX/GPX files

Training Load Analysis:

• calculate_acwr(): Calculate Acute:Chronic Workload Ratio

• calculate_acwr_ewma(): ACWR using exponentially weighted moving averages

• calculate_exposure(): Calculate training load exposure metrics

Physiological Metrics:

• calculate_ef(): Calculate Efficiency Factor (EF)

• calculate_decoupling(): Calculate cardiovascular decoupling

• calculate_pbs(): Calculate personal bests

Visualization:

• plot_acwr(), plot_acwr_enhanced(): Plot ACWR trends

• plot_ef(): Plot Efficiency Factor trends

• plot_decoupling(): Plot decoupling analysis

• plot_exposure(): Plot training load exposure

• plot_pbs(): Plot personal bests progression

Quality Control & Cohort Analysis:

• flag_quality(): Flag activities based on quality criteria

• summarize_quality(): Summarize stream quality flags

• calculate_cohort_reference(): Generate cohort reference bands

Sample Datasets

The package includes simulated datasets for examples and testing:

• sample_acwr: Sample ACWR data

• sample_ef: Sample Efficiency Factor data

• sample_decoupling: Sample decoupling data

• sample_exposure: Sample exposure data

• sample_pbs: Sample personal bests data

Getting Started

library(Athlytics)

# Load your Strava export
activities <- load_local_activities("path/to/strava_export.zip")

# Calculate ACWR
acwr_data <- calculate_acwr(activities, activity_type = "Run")

# Visualize
plot_acwr(acwr_data)

See also

Useful links:

• https://docs.ropensci.org/Athlytics/

• https://github.com/ropensci/Athlytics

• Report bugs at https://github.com/ropensci/Athlytics/issues

• Package website: https://docs.ropensci.org/Athlytics/

• GitHub repository: https://github.com/ropensci/Athlytics

• Strava: https://www.strava.com/

Author

Maintainer: Zhiang He ang@hezhiang.com

Authors:

• Zhiang He ang@hezhiang.com

Other contributors:

• Eunseop Kim (Eunseop Kim reviewed the package (v. 1.0.4) for rOpenSci, see https://github.com/ropensci/software-review/issues/728) [reviewer]

• Simon Nolte (Simon Nolte reviewed the package (v. 1.0.4) for rOpenSci, see https://github.com/ropensci/software-review/issues/728) [reviewer]