A while ago I changed from mean to median with the reasoning being that one spike to a crazy level was not representative of bloat but instead representative of a network stall or other anomaly. Graphs that were nearly all good samples with one outlier were being unfairly graded poorly.
But this example has the opposite issue - the median of this set of samples is the first half where everything is ok. Hence the good score. Using a mean would be correct for this sample.
What should happen is to throw away a couple (max) outliers first, then do a mean to avoid punishing the results that come in as good but include one errant measurement.
thanks
-Justin