Yes, there are several NumPy functions that can be used to compare actual outcomes to expected outcomes:

    numpy.mean(): calculates the arithmetic mean of a given array
    numpy.median(): calculates the median of a given array
    numpy.corrcoef(): calculates the Pearson product-moment correlation coefficients of a given array
    numpy.cov(): calculates the covariance matrix of a given array
    numpy.histogram(): calculates the histogram of a given array and returns the binned values and bin edges
    numpy.percentile(): calculates a specified percentile of a given array
    numpy.std(): calculates the standard deviation of a given array

These functions can be used to analyze the distribution of the actual outcomes and compare them to the expected outcomes.
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