Friday, August 26, 2011

F1 Belgium 2010 - McLaren Telemetry - Hamilton's Gear Usage Round Spa

Telemetry data samples show Hamilton's gear usage during the 2010 Belgian grand prix at Spa, as captured from 1Hz McLaren telemtry data streamed via their live dashboard.

















The node size for zero braking is quite large in the previous images. Here's a view that highlights the actual braking areas:



And here's HAMilton at or near full throttle:



For a great introduction to deciphering the rather more detailed telemetry available to the teams, see ScarbsF1: Telemetry and Data Analysis Introduction

Telemetry data captured (h/t @bencc) from the McLaren F1 Live Dashboard during the race last year, probably Copyright (©) McLaren Marketing Ltd 2010.
Posted by Tony Hirst at 8:22 PM
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3 comments:

  1. Mark HendySeptember 6, 2011 at 10:41 AM

    OK, here goes again. Essentially I wanted to comment to say thanks for this analysis and the visualisation of it. I find this fascinating. I recently been trying to learn a little about data visualisation following the recent surge in popularity and the focus a visualisation can bring to data turning it from data to information. I have recently seen some TED talks video's by Hans Rosling which have provoked my interest further. In one of his talks he presented a balloon race chart and I was wondering if there is commercial or open source software available to create visualisations like this?

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  2. Tony HirstSeptember 6, 2011 at 11:08 AM

    @Mark (Thanks for the comment - apols for any problems posting comments previously... )

    The chart that Hans Rosling used is called a motion chart. Google bought the company and offer the chart as a chart tool http://code.google.com/apis/chart/interactive/docs/gallery/motionchart.html

    There's also a desktop app - http://www.gapminder.org/desktop/ - though I'm not sure if you can run your own data with it.

    I did start to look at trying to generate motion chart based visualisations of F1 races, but at the time my data model was a little broken: http://blog.ouseful.info/2011/04/26/a-first-attempt-at-looking-at-f1-timing-data-in-google-motion-charts-aka-gapminderf/

    I've recently discovered that motion charts can be generated quite easily from within the R statistical programming environment ( http://code.google.com/p/google-motion-charts-with-r/ ), though I haven't tried it out yet...

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