Apparently, winning a gold medal has nothing to do with practice, dedication, athletic prowess, or uh, merit. No, says British statistician Kenneth Mitchell, winning gold depends on your astrological sign. As reported in Reuters:

After comparing the birthdates of every Olympic winner since the modern Games began in 1896, British statistician Kenneth Mitchell discovered gold medals really are written in the stars.

He found athletes born in certain months were more likely to thrive in particular events.

Mitchell dubbed the phenomenon “The Pisces Effect” (pisces is Latin for fish) after finding that athletes born under the sign received around 30 percent more medals than any other star sign in events like swimming and water polo.

…In the history of the Games, the big winners in the overall medals haul were born under the signs of Capricorn, Aquarius and Aries. They boasted a significantly higher number of golds.

Ok, we all know that astrology is complete woo. So what’s going on here?

Many thanks to Mark Chu-Carroll for explaining that this is an example of “pareidolia,” the psychological phenomenon of seeing patterns that don’t actually exist. (One famous example: Percival Lowell thought that the straight lines he saw on the surface of Mars were canals, engineered by Martian life forms. I wrote about what he was actually viewing in my Master’s thesis, pages 5-10.)

As Mark explains:

When we look at large quantities of data, there are bound to be things that look like patterns. In fact, it would be surprising if there weren’t apparent parents for us to find. That’s just the nature of large quantities of data.

…if you look at an arbitrarily chosen 1/4 of the year, athletes with birthdays in that 1/4th of the year have tended to be more likely to win in the Olympics. And note the “significantly higher”, without any numbers to support it. It’s a fake correlation: With 12 astrological signs, you’d expect to be able to find some way of breaking it onto fourths that produced one fourth that included an uneven distribution.

Something tells me that Dr. Mitchell would take much personal offense to Mark’s astute criticisms, though there seems to be no way to find out. The incompetent Reuters journalist Paul Majendie tells us nothing of Mitchell’s academic/institutional/commercial affiliation, nor what part of England he’s from. Majendie says only that Mitchell’s website states: “Just for the record, I know a thing or two about statistics. I have a PhD from Glasgow University on statistical ecology and a further 33 years working on statistical data analysis.” (Thanks for that unbiased opinion.) But I can’t even find this website, nor can I find any credible reference to this “research,” nor any evidence that “Dr.” Mitchell is a working statistician. Perhaps I shouldn’t be surprised; the article also tells us that Mitchell took up this research “after being made redundant from his IT job.” Doh.

(Hat tip: MarkCC; see also The Bad Astronomer)