Once you have an input file you like and have run SIMC, the next step is getting counts out. There are two important pieces to getting results to compare to data. First, you need appropriate cuts. Not only must the cut be identical to the cuts in your data analysis, but they must be CONSISTENT WITH THE VALUES GIVEN IN THE INPUT FILE. This is important because while SIMC will generate events outside of the delta, Em, etc... limits that you give, the normalization will not be correct. Assuming that your xptar and yptar limits cover the full octagon, you should not need additional xptar/yptar cuts in your Ntuple (although you may want them in order to compare to the analysis). You DO need to apply a cut on hsdelta and ssdelta that is at least as tight as the min/max values you use in the input file (SPedge.e(p).delta.min(max)). Similarly, you will need to apply a cut on Em that is equal to or tighter than the cuts.Em.max value. There will be events in the Ntuple beyond your delta and Em limits, due to multiple scattering, energy loss, radiation, and the 'slop' SIMC adds to the generation regions. However, only part of the phase space that contributes to these regions is generated, and so the normalization will be incorrect.
The second thing you need to do is apply the correct normalization.
When looking at the Ntuple you need to apply a weight equal to 
, in order to generate a spectrum representing measured
counts. weight is an entry in the Ntuple (that contains the cross section,
as well as any weight coming from event generation tricks). normfac
comes from the <inputfile>.hist file, and contains the normalization
information from the target thickness, integrated charge, and generation
volume. nevent is the number of events in the Ntuple. Applying this
weight will give the expected counts for whatever charge you gave in
the Ntuple. You will need to apply an additional weight to go from
the simulated charge to the real efficiency corrected charge, if it
is different.