Why is map (slightly) faster then list comprehension in python

Question

I ran into this question about converting ints to floats, and wondered which of the suggested solutions would be faster (and I also was converting to ints, not from them). The code used was this, in ipython:

In [1]: import numpy as np   
In [2]: a1 = np.random.rand(100000)*31  
In [3]: %%timeit
   ...: a2 = [int(a) for a in a1]
   12.3 ms ± 156 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
In [4]: %%timeit
    ...: a2 = list(map(int, a1))
    9.58 ms ± 191 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

So I wonder what's the explanation for this? Is this supposed to work like this? What should I read to get to know more about it?

ETA: this great answer covers the "should this be", but not the "why"