Package: ACWR 0.0.0.9000
ACWR: Acute Chronic Workload Ratio Calculation
Functions for calculating the acute chronic workload ratio using three different methods: exponentially weighted moving average (EWMA), rolling average coupled (RAC) and rolling averaged uncoupled (RAU). Examples of this methods can be found in Williams et al. (2017) <doi:10.1136/bjsports-2016-096589> for EWMA and Windt & Gabbet (2018) for RAC and RAU <doi:10.1136/bjsports-2017-098925>.
Authors:
ACWR_0.0.0.9000.tar.gz
ACWR_0.0.0.9000.zip(r-4.5)ACWR_0.0.0.9000.zip(r-4.4)ACWR_0.0.0.9000.zip(r-4.3)
ACWR_0.0.0.9000.tgz(r-4.4-any)ACWR_0.0.0.9000.tgz(r-4.3-any)
ACWR_0.0.0.9000.tar.gz(r-4.5-noble)ACWR_0.0.0.9000.tar.gz(r-4.4-noble)
ACWR_0.0.0.9000.tgz(r-4.4-emscripten)ACWR_0.0.0.9000.tgz(r-4.3-emscripten)
ACWR.pdf |ACWR.html✨
ACWR/json (API)
NEWS
# Install 'ACWR' in R: |
install.packages('ACWR', repos = c('https://jorgedelro.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jorgedelro/acwr/issues
- training_load - Training load dataframe
Last updated 3 years agofrom:ac3cbbbccd. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | OK | Nov 01 2024 |
R-4.5-linux | OK | Nov 01 2024 |
R-4.4-win | OK | Nov 01 2024 |
R-4.4-mac | OK | Nov 01 2024 |
R-4.3-win | OK | Nov 01 2024 |
R-4.3-mac | OK | Nov 01 2024 |
Exports:ACWREWMAplot_ACWRRACRAU
Dependencies:base64encbslibcachemclidigestevaluatefastmapfontawesomefsgluehighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclememoisemimer2d3R6rappdirsrlangrmarkdownrstudioapisasstinytexxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Acute Chronic Workload Ratio | ACWR |
Exponentially Weighted Moving Average | EWMA |
ACWR plots using d3.js | plot_ACWR |
Rolling Average Coupled | RAC |
Rolling Average Uncoupled | RAU |
Create Training Blocks | training_blocks |
Training load dataframe | training_load |