

Mining Strava's cycling data - ocfnash
http://ocfnash.wordpress.com/2014/05/25/mining-the-strava-data/

======
nl
Interesting. You should link to the segments you are talking about. (Edit: I
see you did now, sorry. Edit2: Wow, Ryan Sherlock has that KOM in Ireland and
the KOM on Old La Honda in California. Nice work by a non-Protour rider!)

 _Amongst the questions that I thought it might be interesting to attack are
the following.._

I think you'll find many people are using Strava data to attack the problem of
developing a model for maximal power output over time. Veloclinc[1] and
DJConnel[2] are probably the best places to start for reading about this.

The "cleaning data" section surprised me. In my experience maybe 10% of
(manually inspected) efforts have significant problems, but you seem to have
thrown away a lot more than that on Col du Tourmalet and Alpe d’Huez. Stocking
Lane looks roughly in the order I'd expect. Any idea what is going on there?

 _it is likely that a person will cycle a 15% gradient towards the end of a
climb more slowly than the 15% near the beginning._

Not really. Judging your maximum speed on a climb is a significant problem and
it goes both ways (especially on faster cyclists). Hence the "Chris Froome
looking at his stem" meme[3] - he is notorious for climbing based on power
output (which maximises your overall velocity).

Regarding altitude, you are best to look at the device the data came from.
Phones are notorious for getting altitude data wrong, whereas Garmin devices
are pretty good. Using Google data is mixed: the gradient of the road changes
significantly depending what line you take, and that isn't replicated in
Google's data.

Regarding your power equation, you realize Strava already does this (as power
estimates), right? [4] is a pretty decent Javascript version. The problem is
that it is _very_ weight dependant, and getting an exact weight for a
bike+rider+clothes is pretty hard from random Strava data.

[1] Hard to read, but eg: [http://veloclinic.tumblr.com/post/85194606798/ward-
smith-cp-...](http://veloclinic.tumblr.com/post/85194606798/ward-smith-cp-vs-
wko4-ftp-if-you-use-the-correct)

[2] eg: [http://djconnel.blogspot.com.au/2014/05/numerical-testing-
of...](http://djconnel.blogspot.com.au/2014/05/numerical-testing-of-maximal-
power.html)

[3]
[http://chrisfroomelookingatstems.tumblr.com/](http://chrisfroomelookingatstems.tumblr.com/)

[4]
[http://www.kreuzotter.de/english/espeed.htm](http://www.kreuzotter.de/english/espeed.htm)

~~~
thrownaway2424
Android vs. Garmin altitude data seems like an irrelevant distinction, as
Strava keeps and maintains forever the altitude profile of the very first
person who rode from A to B, no matter how ridiculous the data. On the route I
ride most often, up Tunnel Rd in Oakland, California, it's a climb of about
1000 feet over about 4 miles, depending on where you reckon the start and end,
but on the whole length it's just monotonically uphill. There are no down
grades. But the Strava data is all over the place. It goes up and down on
small scales constantly. It says there's a -47% grade at one point. The
profile looks like the business end of a backsaw, when in reality it's just
up.

To make any sense of this data requires substantial low-pass filtering over
their altitude data. I don't know why Strava doesn't try to clean this up.

~~~
paulmach
Using the API you can get both the Segment altitude data and the Segment
Effort altitude data. The segment data is what's displayed on the website and
can be bad. But the Segment Effort data would be a subset of the data from the
activity. So you can get many many versions of the altitude for the segment
and do any type of analysis you wish.

~~~
nl
Can I ask why Strava doesn't do something about the Segment altitude data?

~~~
paulmach
Priorities....

------
keithg
If you guys are interested in data-mining Strava, here is some interesting
info on their metro project and how they are using it to affect change.

[http://blog.strava.com/arent-we-all-people-for-
bikes-7783/](http://blog.strava.com/arent-we-all-people-for-bikes-7783/)

[http://metro.strava.com/](http://metro.strava.com/)

