We collect more and more data and it is becoming increasingly difficult to make meaning out of it. What I would like to do is to present one simple way to make the meaning out of session GPS data using LOF and Clustering…
I have recently read two great papers on using alternative metrics when analyzing countermovement jump (CMJ) with the goal of evaluating both acute (neuromuscular fatigue, or NMF) and chronic training effects written by …
Here is the another ‘playbook’, but this time on my own data set during high-frequency project I did in 2013. The data set features estimated 1RM using velocity (which I measure during the lifts). I have also measure…
In the previous part I’ve introduced multivariate modeling of impulse and response using Banister model. In this part I will continue with exploration of this model, mainly visualizing reaction predicted by the model o…
Banister Impulse~Response Model in R Before you start reading this post, please read EXCELLENT paper by Clark and Skiba, especially on the topic of Banister impulse-response model. I decided to write code in R, but also …
I have just started reading about machine learning and predictive analytics in general, so I wanted to share my planned journey for those who wish to start the same.
In this video, I go over the usual problems of calculating total Wellness from different categories and I present a new way to calculate total wellness score that is more sensitive.
I am just reading Data Science for Business book, which is by the way great, and finishing Discovering Statistics Using R. Both of these provide interesting viewpoint on building models. In most other stats books, linear…
It is pretty common to use generic %1RM tables when prescribing weight training, both for upper body and lower body movements. As with everything, there are pros and cons of such an approach...
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