By Mladen Jovanovic on 07/03/2017
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, philosophy of science, heuristics and practical experience as coach & sport scientist into one article. Hopefully I managed to create readable narrative.
By Mladen Jovanovic on 08/12/2016
In the following article, I am discussing the famous “J” curve in injury prediction, as well as simulate some data to show how that curve is estimated. I also show the distinction between association and prediction, as well as how to make training decisions based on the different costs of committing false positive and false negative errors.
By Mladen Jovanovic on 29/06/2016
In the following article I am reviewing very interesting article by Windt, Gabbett et al.: “Training load–injury paradox: is greater preseason participation associated with lower in-season injury risk in elite rugby league players?”.
By Mladen Jovanovic on 02/11/2015
This is the problem I have been wrestling with for some time and I tried to solve it using Bannister model. I even asked for help on Twitter and couple of data scientists suggested taking a look into “functional data analysis” or creating summary variables and performing regression/classification (which I did here).
By Mladen Jovanovic on 25/08/2015
In this first episode of Complementary Training Podcast I pick the brain of Žarko Vučković, general surgeon working at Aspetar on the topic of groin-related pain.
We cover plenty of ground, including the different “categories” of groin-related issues (sport hernia, adductor issues, hip flexor, hip issue and so forth), screening tests and clinical examination, prevention strategies, surgery decision making, surgical…