This post follows from the Accessing the Golden Cheetah OpenData post. This gist starts the process of developing an interval detection algorithm utilizing statistical change point detection. For python ‘ruptures’ is a library that offer several options for change point detection.

# Category: Uncategorized

## A Transverse Doping Probability Passport: A Conceptual Illustration

Athlete doping rarely happens in isolation. So why do ADAs try to tackle the problem that way? Consider this toy model of the social structure of a doping network. We may have individuals who may be Athletes, Trainers, Coaches, and Doctors. The individuals may instigate doping behavior, be reactive to doping behavior (dope if pressured, …

## GoldenR Cheetah Script for Visualizing Delta W’balance By Interval

In the white is Skiba’s W’balance that you all know and love. I’ve combined this now with the interval discovery algorithm so that we can now visualize the change in W’bal by interval in green. ## R script will run on selection. ## ## GC.activity() ## GC.metrics(all=FALSE) ## ## Get the current ride or metrics …

## GoldenR Cheetah Script For Interval Discovery

The Golden Cheetah crew has now integrated R into Golden Cheetah in the latest development build. This update instantly gave Golden Cheetah statistical and modelling super-powers to the point where I gave it the nickname GoldenR Cheetah. As an example, this script uses the change point package to auto discover intervals within a power file. …

## Estimating the Probability of Doping as a Function of Power

A repeating theme heard in performance analysis discussions is that “Performance doesn’t prove doping.” Of course this is true because proof, as an absolute, doesn’t really exist. Instead, most real-world evidence driven judgments are based on probability and not “proof.” From this perspective, this post will illustrate the concept of using a mathematical model to …

## Athlete Biological Passport For Level Change Detection

One of the weaknesses of the current Athlete Biological Passport software seems to be an over-emphasis on outlier detection versus level change detection. To illustrate this point consider the Lance Armstrong case: According to the UCI, Armstrongs blood data never triggered a flag on the software. The software screen was non-positive despite the obvious …

## 2014 Giro d’Italia Climb Preview

The upcoming 2014 Giro d’Italia features 6 that are likely to play a role in shaping the final podium. As with previous Grand Tours, @ammattipyoraily is my go to source for the most consistent data. The process is simple: 1. Measure the climbs. 2. Time the finishing climbs. 3. Estimate normalized W/kg power outputs using …