Most of us are collecting and analyzing training load data and readiness metrics (i.e. GPS training load, sRPE and wellness). The most common analysis method is to use two rolling averages windows – acute (around 7 day…
In my opinion, biomotor abilities are ‘dimension reduction’ of the complex perceptual-motor space. Suppose we perform 500 various tests of performance for at least 5000 athletes.
In this video I am explaining two methods to deal with missing values and why you should pay attention to the way you are aggregating data (daily, team averages, body soreness, etc).
I also love to call this problem “Terminator Problem”, since it is more understandable to coaches, since most of them have seen Terminator movies. The issue is, once we are able to “predict” the future (for examp…
Sean Williams was kind enough to provide short review of the recent load monitoring workshop, held at the World Rugby Science Network Conference, as well as to provide full slides and Excel templates. This is tremendous …
I stumbled on Robert Frederic by accident, probably through Facebook. So, after exchanging few messages with him, I decided to do a video interview and a Q&A regarding the “exertion load” metric, as well as his app. …
In this video I am deploying the model to make the decision between 5 variations of weekly plan. The goal is to minimize the morning soreness on the day of the game.
In this video I am presenting my “solution” to the problem and provide fake data set, as well as R code for analyzing the data. Having decent predictive model can help us run different optimization algorithms to find…
The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without t…
I was asked by Rod Whiteley and Nicol van Dyk to contribute to the Aspetar Journal targeted topic issue that just got released off the press. I tried to combine my knowledge of predictive analytics, machine learning, phi…
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