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Science predicts athletes’ potential
We’ve been pretty in awe of science lately. Whether its reaching a breakthrough in Alzheimers’ treatment, making self-healing concrete or designing on a bionic brain, scientists are working around the clock on groundbreaking research that will objectively make the world a better place.
And then occasionally there’s research that makes us scratch our heads and go, “well, that’s neat… but isn’t there something more productive they could be doing?” Yeah, yeah – ‘people in glass houses,’ we know.
Anyway, research from Humboldt University of Berlin and University College London has found an algorithm that can predict athlete’s potential over distances that they don’t typically race.
To do this, the scientists measured data from 1.5 million runners over distances ranging from 100 meters to a full 26.2 mile marathon. They developed an algorithm that measures overall performance, endurance versus speed and preferred distance to predict the result over any other distance – with some surprising results.
They posit, for example, that Kenenisa Bekele who holds the 5,000 and 10,000 meter world records should also have a marathon record beating time of 2:00:36 in him. They also reckon that British 100-meter sprinter Adam Gemili should be able to break the 400 meter record with a time of 43.2 seconds.
Well, there’s only one way to find out.
Perhaps most intriguingly, though, is it finally puts to bed a question that’s been bugging athletics fans since the 2012 Olympics: what would be a fair race between Usain Bolt and Mo Farah? The former holds the world record for the 100 meter sprint, while the latter won Gold at the 2012 Olympic 10,000 meter distance run. Crossover, according to the researchers, would come at exactly 492 meters. Best get designing that track.
No algorithm can account for someone’s best possible Beer Mile time, though. We smell a follow-up paper.
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