  In competitions involving many participants running many races the final rank
is determined by the score of each participant, obtained by adding its ranks in
each individual race. The "Statistical Curse of the Second Half Rank" is the
observation that if the score of a participant is even modestly worse than the
middle score, then its final rank will be much worse (that is, much further
away from the middle rank) than might have been expected. We give an
explanation of this effect for the case of a large number of races using the
Central Limit Theorem. We present exact quantitative results in this limit and
demonstrate that the score probability distribution will be gaussian with
scores packing near the center. We also derive the final rank probability
distribution for the case of two races and we present some exact formulae
verified by numerical simulations for the case of three races. The variant in
which the worst result of each boat is dropped from its final score is also
analyzed and solved for the case of two races.
