The generalized efficient markets (GEM) principle says, roughly, that things that would give you a big windfall of money and/or status, will not be easy. If such an opportunity were available, someone else would have already taken it.
In a sense sufficient to circumvent GEM, is not as hard as it might seem at first glance (though that doesn’t exactly make it easy). The trick is to exploit dimensionality.
Consider: becoming one of the world’s top experts in proteomics is hard. Becoming one of the world’s top experts in macroeconomic modeling is hard. But how hard is it to become sufficiently expert in proteomics and macroeconomic modeling that nobody is better than you at both simultaneously? In other words, how hard is it to reach the Pareto frontier?
For GEM purposes, elbow room matters. Maybe I’m on the Pareto frontier of Bayesian statistics and gerontology, but if there’s one person just a little bit better at statistics and worse at gerontology than me, and another person just a little bit better at gerontology and worse at statistics, then GEM only gives me the advantage over a tiny little chunk of the skill-space.
Claiming a spot on a Pareto frontier gives you some chunk of the skill space to call your own. But that’s only useful to the extent that your territory contains useful problems.
Two pieces factor in here. First, how large a territory can you claim? This is about elbow room. Second, what’s the density of useful problems within this region of skill space? The table tennis/sprinting space doesn’t have a whole lot going on.
One problem with this whole GEM-vs-Pareto concept: if chasing a Pareto frontier makes it easier to circumvent GEM and gain a big windfall, then why doesn’t everyone chase a Pareto frontier? Apply GEM to the entire system: why haven’t people already picked up the opportunities lying on all these Pareto frontiers?
Answer: Dimensionality. If there are 100 different specialties, then there are only 100 people who are the best within their specialty. But there are 10k pairs of specialties (e.g. statistics/gerontology), 1M triples (e.g. statistics/gerontology/macroeconomics), and something like 10^30 combinations of specialties. And each of those Pareto frontiers has room for more than one person, even allowing for elbow room. Even if only a small fraction of those combinations are useful, there’s still a lot of space to stake out a territory.