by Andrie de Vries
A week ago my high school friend, @XLRunner, sent me a link to the article “How Zach Bitter Ran 100 Miles in Less Than 12 Hours“. Zach’s effort was rewarded with the American record for the 100 mile event.
This reminded me of some analysis I did, many years ago, of the world record speeds for various running distances. The International Amateur Athletics Federation (IAAF) keeps track of world records for distances from 100m up to the marathon (42km). The distances longer than 42km do not fall in the IAAF event list, but these are also tracked by various other organisations.
You can find a list of IAAF world records at Wikipedia, and a list of ultramarathon world best times at Wikepedia.
I extracted only the mens running events from these lists, and used R to plot the average running speeds for these records:
You can immediately see that the speed declines very rapidly from the sprint events. Perhaps it would be better to plot this using a logarithmic x-scale, adding some labels at the same time. I also added some colour for what I call standard events – where “standard” is the type of distance you would see regularly at a world championships or olympic games. Thus the mile is “standard”, but the 2,000m race is not.
Now our data points are in somewhat more of a straight line, meaning we could consider fitting a linear regression.
However, it seems that there might be two kinks in the line:
- The first kink occurs somewhere between the 800m distance and the mile. It seems that the sprinting distances (and the 800m is sometimes called a long sprint) has different dynamics from the events …read more
Source:: http://revolutionanalytics.com