De vloek van de regenboogtrui onderzocht

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The curse of the rainbow jersey probably does not exist. The current road racing world champion wins less on average than he did in the previous season, but this phenomenon is best explained by regression to the mean. The relative lack of success was not restricted to the season in the rainbow jersey but persisted in the following season and affected equally the winners of the Tour of Lombardy. There was nothing remarkable about the year spent wearing the rainbow jersey.

Nevertheless, this study may not rule out a curse entirely, as it tested only one facet of the curse—the decrease in wins. I found no good data about the personal problems of professional cyclists. Also, all wins were given even weight: if the world champion is cursed to winning only minor races, this analysis would have missed that. Finally, this analysis did not account for any changes in doping practices, for lack of reliable data. The possibility remains that cyclists dope until they win an important race and stop afterwards.

Regression towards the mean is unavoidable whenever the variable under study (here, sporting success) fluctuates over time, the correlation between consecutive observations is less than 1, and the baseline observation is defined by an arbitrarily high or low value (here, a season marked by an important win). Regression to the mean may explain, for instance, why patients who lose bone density in the first year are likely to reverse this trend at follow-up or why HIV related risk behaviours improve after enrolment into a prevention trial.7 8 This phenomenon occurs regularly in clinical medicine, research, and programme evaluation, as well as in other walks of life. For instance, some flight instructors believe that praising a pilot after a smooth landing is counterproductive but reprimanding a pilot after a rough landing leads to improvement.2 Their observation is correct—an extreme performance will be followed by a more average one—but the causal inference is not. Neither is this reaction particularly new. Quite possibly the proverb “Pride goeth before destruction” (King James Bible, Proverbs 16:18) should be credited with the first description of regression towards the mean, and not Francis Galton,9 who merely showed that chance and correlation, not the Lord or a large ego, were to blame.

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Several riders won more than one target race, and 63 different riders contributed data: 40 riders had one target win, 14 had two wins, seven had three wins, one had four wins, and one had five (Merckx, triple world champion and double Lombardy winner). Six riders won both races in the same season.

Winners of both target races had similar annual numbers of wins: on average 4.18 (quartiles 1, 2.5, and 5) for world champions, and 4.37 (quartiles 1, 3, and 6) for Lombardy winners. Similarly, for winners of both races, the annual win total was higher in year 0 than in years 1 and 2 (table 1⇓); the difference between year 0 and the following years was statistically significant, but the difference between years 1 and 2 was not.