  The Olympic Games are the largest, highest-profile, and most expensive
megaevent hosted by cities and nations. Average sports-related costs of hosting
are $12.0 billion. Non-sports-related costs are typically several times that.
Every Olympics since 1960 has run over budget, at an average of 172 percent in
real terms, the highest overrun on record for any type of megaproject. The
paper tests theoretical statistical distributions against empirical data for
the costs of the Games, in order to explain the cost risks faced by host cities
and nations. It is documented, for the first time, that cost and cost overrun
for the Games follow a power-law distribution. Olympic costs are subject to
infinite mean and variance, with dire consequences for predictability and
planning. We name this phenomenon "regression to the tail": it is only a matter
of time until a new extreme event occurs, with an overrun larger than the
largest so far, and thus more disruptive and less plannable. The generative
mechanism for the Olympic power law is identified as strong convexity prompted
by six causal drivers: irreversibility, fixed deadlines, the Blank Check
Syndrome, tight coupling, long planning horizons, and an Eternal Beginner
Syndrome. The power law explains why the Games are so difficult to plan and
manage successfully, and why cities and nations should think twice before
bidding to host. Based on the power law, two heuristics are identified for
better decision making on hosting. Finally, the paper develops measures for
good practice in planning and managing the Games, including how to mitigate the
extreme risks of the Olympic power law.
