ok colonels, here is your argument.
lets simplify the sim to a somewhat comparable model to examine the effect of randomness on the outcomes.
in the sim, not that many shots are taken by a team in a half. there are also a whole bunch of other coin flips, but many have less weight than each shot. also, there are 2 and 3 pointers. but to simplify, lets say there are 80 1 point shots being taken, and no other randoms involved. in reality, 2 and 3 pointers are more volatile, but things like, which defensive player tries to get the rebound, are less volatile. so this seems like a reasonable middle ground.
so, we have 80 equal weight coin flips for each team. team 1, the superior team, is shooting about 50% fgs against a weak schedule. his opponent is somewhat weaker than his schedule, but he was on the road, so lets stick with 50% for his probability of making each point. team 2, the inferior sim team, is shooting 42% against a significantly weaker schedule than his opponent, who crushed him. so lets go with 35%.
anyway, the expectation of team 1 is to make 40 shots, for 40 points. the probability of this event is 8.8%. The probability of the event in the sim, of team 1 making 50 shots, is .7%. that's a little under 10 times as likely as the expected outcome. so really, nothing surprising there.
the expectation of team 2 is to make 28 shots. the probability of this event is 9.3%. in the sim, team 2 only makes 9 points, which has a probability of 9.5 times 10^(-7). this is approx 100 thousand times less likely than the expected outcome.
with about 10K games simmed per day, and 20K halves, i don't think seeing an outcome that is 1 in 100K is particularly surprising. with 20K halves, i would expect a larger outlier than that on a daily basis.
as we have discussed before, i think it is extremely difficult to hang your hat on any single example and proclaim the sim is broken. if we took a sampling of say a hundred or thousand games a day for 10 days, and looked at those results, then an argument might be able to be made that the occurrence of unlikely events was not in line with what you would expect from simple randomization of every event.
i personally would not be surprised to see there were too make unlikely events. i am kind of on the fence, wouldn't be surprised either way, maybe even leaning towards expecting "too many". and my best guess would be that it is a result of a random factor that applies to more than a single coin flip, which would certainly skew the results from when we would expect if it was significant. for example, if there was a random factor on the weight of HCA which was applied to a large number of the coin flips in a simulation, it would throw off the normal bell curve we would expect considerably (IMO at least).