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Big Data Helping Us Run Faster

by Dan Gray
May 9, 2014
in Uncategorized
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Previously we had a look at how data-centric approaches were used in baseball and cricket to identify undervalued players. Today we review studies on absolute limits on how fast humans and animals can run.

While human runners continue to set new speed records, racehorses appear to have reached a plateau. The Kentucky Derby has been won in just over two minutes every year since 1949. Usain Bolt’s world-record time of 9.58 seconds for the 100-meter race was only set in 2009.

Statistical analysis suggests that the fastest time possible for a human is 9.48 seconds. However, like most correlation-based studies, such an approach does not indicate why this is the case.

A plausible explanation is genetic diversity. American racehorses are bred from a small gene pool, with 95 percent descending from a single 18th-century horse. Now compare 25,000 racehorses born each year in the US to 7 billion people worldwide. The size of the human population suggests a larger number of athletes with extreme speed.

The next question is whether this presents a case for genetic engineering. The ban on cloned racehorses has been controversial, and eventually lifted in 2012. Perhaps one day we may even see a race between clones of well-known racehorses, or even between identical clones of the same horse.


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Read the full article here.

In conjunction with Big Data Week, we compiled a list of the best Big Data articles here.

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