Athlete Monitoring: Data Analysis and Visualization
Introducing athletemonitoring R package
Athletemonitoring R-language package started as my attempt to create an easy way to aggregate, analyze, and visualize training monitoring data from the AthleteSR. Since I had to create a way to easily analyze monitoring data without a priori knowledge about it, I had to write more universal/general functions. And as such, they could be used across various scenarios. These involve dealing with missing entries, missing days (or levels of analysis), aggregating data (i.e., multiple sessions in a single day), rolling functions, and comparing individual vs. group trends. In other words, all the issues that we have covered in this course thus far.
I am hoping that this package will help researchers and sports scientists perform the common data aggregation (e.g., acute and chronic rolling averages) that allow easy reproducibility, particularly for the research.
In this module, I am going to introduce athletemonitoring package by demonstrating how easy is to perform common data analysis and deal with issues explained in the previous modules. I will also demonstrate the AthleteSR software (which is free for the Complementary Training members), how to extract/sync the monitoring data from it, and how to analyze it in the simple dashboard that uses athletemonitoring and Shiny R extension (or if you want to do it by hand using R).
The first video introduces the athletemonitoring package and how to install it, outlines the package functionalities, and where to ask for help and extra features to be developed.