This web application is free, but if find CRplots.com useful and would like to help support it, feel free to make a small donation!
This is a small and simple web-application that displays an analysis of run training from data held on Strava.
I (Christof Schwiening) wrote the application. The application caches a copy of your running data (distances, times, heart rates) on an independent Server to allow for processing. This data is just a small part of what Strava holds on you. Whilst I maintain good security practices I cannot guarantee perfect protection of your data.
I will be able to inspect your data, necessary for implementing future functions. If you are uncomfortable with this, please do not use the application.
I will not comment, discuss, disseminate or contact you about your data unless requested to. Should you contact me (firstname.lastname@example.org) I will be able to offer you advice on the processing of your data (time constraints allowing), but I am not a coach.
The application does NOT give me any access to changing any settings on your Strava account - all it allows for is the reading of your activities.
To understand the implications of the plots requires some knowledge - especially about what I mean when I plot a 'Tanda' Day. The Tanda bit refers to Giovanni Tanda who ed a paper suggesting that marathon performance can be predicted from simply the distance you run in an eight week period and the time it took. I have written about it here. I first came across the paper in 2014 - at a point where no one was talking about it. The surprise was how well his formula had predicted my past marathons [I have a 0 offset from his prediction, you may out or under perform the predictive equation].
Read the blog posts if you want to know more. The important feature is that the Tanda prediction does correlate well with improved marathon performance.
If you can improve your eight week Tanda prediction then (all other things being equal) will probably be able to race a faster marathon - but, I make no promises.
Christof Schwiening, Cambridge, November 2019