Was thinking a bit about the different kinds of maps, specifically regarding production distribution. Some maps seem to place more emphasis on controlling the right regions than others.
I then had an idea: to use the Gini coefficient to measure the distribution of production within maps. Pretend that each site is a person and the map is the nation; each site's production is effectively its income. Luckily, this is pretty easy to calculate too!
Here's a fairly golfed 3-line calculator (relies on numpy because I was lazy, sorry, but should be easy to rewrite it to not use numpy ):
import sys, json, numpy
prods = numpy.cumsum(sorted(numpy.array(json.loads(open(sys.argv, 'r').read())['productions']).flatten()))
Pass it the filename of the replay as the command line argument.
I tried it on a sample replay (specifically
ar1482947270-2437412300.hlt) and got a coefficient of 0.306, which is appreciably less than the US and on par with a country such as Hungary.