Athlete Monitoring: Data Analysis and Visualization

In the Athlete Monitoring course, we will build things from the ground up. You will learn different data types, different data formats, their pros and cons, how to aggregate and smooth the data, and much more.
Mladen Jovanović · December 10, 2020

Athlete monitoring is more than flashy graphs and dashboards. Athlete monitoring is a complex process of collecting the data, tagging and understanding metrics, wrangling and preparing the data, dealing with missing values and measurement error, deciding the best way to explore, plot, and model the data given the question at hand, understanding underlying assumptions and finally making decisions and inferences.

In the Athlete Monitoring course, we will build things from the ground up. You will learn different data types, different data formats, their pros and cons, how to aggregate and smooth the data, and much more. I will show you what can be done in Microsoft Excel and what can be much more easily done in an open-source R programming language using the {athletemonitoring} package. You will learn to wrangle the data, aggregate, describe, visualize, and model. I will show you how to create neat visualizations and dashboards. As a more advanced topic, I will show you how to generate dose-response models using the {dorem} package.

You might be wondering if this course is for you. If you collect any data from yourself or your athletes or your organization, this course is a must. This course will not only give you the knowledge, but it will also give you the tools that you can use immediately.

What are you waiting for? Sign-up, grab a coffee, and let’s go!

About Instructor

Mladen Jovanović

Mladen Jovanovic is a physical preparation coach from Belgrade, Serbia, grew up in Pula, Croatia (which he considers his home town). He was involved in physical preparation of professional, amateur and recreational athletes of various ages in sports such as basketball, soccer, volleyball, martial arts and tennis. Email | LinkedIn | Twitter | Facebook

4 Courses

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Course Includes

  • 26 Lessons

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