Expert debunks the 'curse of the rainbow jersey'

The cycling World champion is significantly less successful during the year when he wears the rainbow jersey than in the previous year, but this is not due to a curse, as many believe, according to a study in the Christmas issue of The BMJ.

The "rainbow" jersey is worn by the current cycling World champion (it is white, with bands of blue, red, black, yellow and green across the chest), explains Thomas Perneger at Geneva University Hospital, Switzerland.

Many cyclists believe that the World champion will be afflicted with all manner of misery while wearing the jersey- injury, disease, family tragedy, doping investigations, even death - but especially a lack of wins.

Theories include the "spotlight effect" (people notice when a champion loses), the "marked man hypothesis" (the champion, who must wear a visible jersey, is marked closely by competitors), and "regression to the mean" (a successful season will be generally followed by a less successful one - the phenomenon of 'averaging out' in statistics).

So Dr Perneger decided to test to what extent these theories are supported by racing results of cycling champions.

He identified winners of the Union Cycliste Internatinale mens' World championship road race or the Tour of Lombardy from 1965 to 2013.

He then analysed the number of professional wins per season in the year when the target race was won (year 0), and in the two following years (year 1 and 2); the World champion wears the rainbow jersey in year 1.

On average, he found that World champions registered 5.04 wins in year 0, 3.96 in year 1, and 3.47 in year 2; meanwhile winners of the Tour of Lombardy registered 5.08, 4.22 and 3.83 wins.

A mathematical model revealed that the baseline year accrued more wins than the other years, but the year in the rainbow jersey did not differ significantly from other cycling seasons.

Dr Perneger concludes that the cycling World champion "is significantly less successful during the year when he wears the rainbow jersey than in the previous year, but this is best explained by regression to the mean, not by a curse."

He notes that mistaking regression to the mean for the effect of treatment is is also a common error made by doctors and patients.