You can show that the max is a comprehensively better estimator than twice the mean.

This is one of the rare cases where you can outperform the mean by a large margin.

The standard deviation of the mean-based estimator, which measures its accuracy, will go down like 1/sqrt(n) where n is the number of samples in the finite set. This is the rate standardly seen in lots of estimation problems.

But the standard deviation of the max-based estimator will go down like 1/n, a much faster rate. That's one manifestation of the "weirdness" of this problem. It means you can get surprisingly good estimates of the number of tanks considering the small numbers of observations.