Posts tagged with ‘Visualization’

  • “Novel” Metric to Compare Athletes Using Their Load-Velocity Curve

    By Mladen Jovanovic on 15/07/2015

    The question is simple: “What could be used to compare athletes across time and among themselves, taking into account the full load-velocity continuum, but taking into account their strength levels and body weight?”. You can find my answer here

  • R Playbook: Introduction to Multilevel/Hierarchical Models

    By Mladen Jovanovic on 09/07/2015

    I wrote about mixed-level models before and I want to expand on it here. I sort-of finished Andrew Gelman’s Data Analysis Using Regression and Multilevel/Hierarchical Models and will continue to play with it. As far as I know Andrew uses the term multilevel models and avoids the terms fixed and random effect. This is a great book to have.


  • Velocity Based Strength Training Workshop

    By Mladen Jovanovic on 28/06/2015

    I knew I was preaching to the choir of experienced coaches, so I wanted to cover practical applications of the VBT as one “novel” way of prescribing and controlling training. I thought live testing would be much more appreciated than fancy graphs and theory, as it would also show the problems of “when the rubber meets the road” issues...

  • R Playbook: Introduction to Mixed-Models

    By Mladen Jovanovic on 24/03/2015

    I just started reading more about mixed-models (multilevel/hierarchical) and will use this as a playbook. Mostly because I learn the best by experimenting with the data and I suggest everyone to try to do the same. So please note that this is just a published playbook – if you find it useful, great, if you find some errors, please…

  • AFL Game GPS Stats Analytics Workbook

    By Mladen Jovanovic on 14/03/2015

    Keith Lyons shared one game of data for one AFL game across four quarters for the #UCSIA15 course. I took some time to analyze it using R and created interactive and reproducible document (HTML) using knitr and markdown. You can download markdown file and CSV data file HERE

  • Making Sense Out of the Session GPS Data

    By Mladen Jovanovic on 06/11/2014

    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. Most GPS units produce multiple features p compared to number of observations n, so we are…

  • Couple Ideas to Make AMS Products Better

    By Mladen Jovanovic on 06/07/2014

    Couple Ideas to Make AMS Products Better Here are couple of ideas/random thoughts to make Athlete Management Software (e.g SMARTABASE, EDGE10) better. AMS should be simple as possible. If one can’t use it, if it takes too much time to learn it, or it is not intuitive, then what’s the point? Bragging on how much you paid for it?...

  • What Are Biomotor Abilities?

    By Mladen Jovanovic on 01/07/2014

    Do you know what are biomotor abilities? How did they ‘emerge’? The purpose of this video is to explain to you the ontology of biomotor abilities, the certain flaws of their use (The Root problem, buckets, periodization based on those qualities) and also provide statistical analysis in RStudio with simulated data using Factor Analysis and Hierarchical Clustering.

  • Playbook: Exploring decathlon competition data. Part 2

    By Mladen Jovanovic on 18/05/2014

    Playbook: Exploring Decathlon Competition Data Click HERE to read part 1   Clustering What we might be interested next is similarities between athletes, or in other words, which athletes have similar profiles. For that purpose we can use Hierarchical Clustering and Principal Component Analysis (PCA) which we are going to cover later HCWard <- hclust(d = dist(decathlon.normal),...

  • Playbook: Exploring decathlon competition data [Part 1]

    By Mladen Jovanovic on 17/05/2014

    Playbook: Exploring Decathlon Competition Data Data set Decathlon data set comes from FactoMineR package and represents two competitions: Decastar and Olympic Games. For this example we will explore only Olympic Games competition, so we need to subset the data. # Load the needed packages library(FactoMineR) library(ggplot2) library(reshape2) suppressPackageStartupMessages(library(googleVis)) # Load the decathlon data data(decathlon) # Subset the...