About randomness and minmax algorithm with alpha beta pruning

Will choosing the child of a node randomly in the alpha beta algorithm have a better chance to get a cut off than choosing them in order?

Here's the pseudocode with my addition marked with ***.

function alphabeta(node, depth, α, β, maximizingPlayer)
     if depth = 0 or node is a terminal node
         return the heuristic value of node
     arrange childs of node randomly ***
     if maximizingPlayer
         v := -∞
         for each child of node
             v := max(v, alphabeta(child, depth - 1, α, β, FALSE))
             α := max(α, v)
             if β ≤ α
                 break (* β cut-off*)
         return v
     else
         v := ∞
         for each child of node
             v := min(v, alphabeta(child, depth - 1, α, β, TRUE))
             β := min(β, v)
             if β ≤ α
                 break (* α cut-off*)
         return v

I ran a small sample with this on a connect four game and it does seem to run a little faster, but when I actually count the cutoffs with and without randomness, there are more cutoffs without randomness. That's a little odd.

Is it possible to prove that it's faster (or slower)?