R for Sport Scientists – Fundamentals Course: SubsettingBy Mladen Jovanovic on 05/11/2021
In this lecture, I will explain to you how subsetting works, how you can replace (i.e., assign) parts of the object, remove parts, append objects, order, and filter. These operations are one of the most important ones in any analysis that you might perform later.0
R for Sport Scientists – Fundamentals Course: VectorsBy Mladen Jovanovic on 27/10/2021
In this lecture, I will provide you with a must-needed knowledge of understanding the R objects with special attention to the vectors.
R for Sport Scientists – Fundamentals Course: InstallationBy Mladen Jovanovic on 11/10/2021
In this lecture, I will show you how to install R and R Studio. In addition to these, I will explain how to install packages both from CRAN and Github repositories.
R for Sport Scientists – Fundamentals Course: IntroductionBy Mladen Jovanovic on 01/10/2021
In this lecture, I will go over a course outline, explain why you need to learn R, how to learn it, and where to find more information once this course is done.
R for Sport Scientists – Fundamentals CourseBy Mladen Jovanovic on 29/09/2021
This course will give you the essential knowledge that will allow you to start coding in R and embrace the R journey much more quickly. So, grab a coffee, and let’s do this first step of the thousand miles journey together!
Mladenverse: Collection of R PackagesBy Mladen Jovanovic on 18/01/2021
2020 was a tough year for many. I took the lockdown as an opportunity to finish some old projects, start new ones, and learn new skills.
Force-Velocity Profiling and Training Optimization CourseBy Mladen Jovanovic on 30/07/2020
Are you interested in force-velocity profiling but don't know where to start, nor you have the tools to perform the analysis? Look no further - this course will help you learn the necessary skill and provide the needed tools.
Extending the Classical Test Theory with Circular Performance ModelBy Mladen Jovanovic on 13/01/2020
In this video, I will go more into these details and also provide an extension of this model, which I termed Circular Performance Model (CPM). CPM, in my opinion, better represent performance phenomenology we experience as coaches and athletes.
Statistical 101: Gender Salary GapBy Mladen Jovanovic on 24/01/2019
With this short article I wanted to showcase how easy is to jump to conclusions with simplistic statistical analysis using fake salary data. It is important to recognize that statistical analysis involve a lot of subjective decisions and cannot be claimed to be purely objective, but it is still way better than ignorance or ideology.
Predicting Non-contact Hamstring Injuries by Using Training Load Data and Machine Learning ModelsBy Mladen Jovanovic on 17/12/2018
Research has shown that there is an association between training load and likelihood of suffering non-contact injuries. But can we predict the injury? In this paper I have tried to predict non-contact hamstring injury by using two seasons day-to-day training load data.