Levenshtein's classical theorem shows that any code that can uniquely decode from \(t\) deletions can also uniquely decode from \(t\) insertions. This symmetry, however, does not generally hold in the list-decoding regime. Several prior results on the capacity and radii of list-decoding from insertions and deletions suggest that insertions are easier to handle than deletions. In an effort to better understand this asymmetry between insertions and deletions under list-decoding, we study an analogous version of McEliece's \emph{average list size problem}. More precisely, given a binary code \(\mathcal{C}\) of length \(n\) that uniquely corrects \(t'\) insertions (or deletions), we are interested in the average number of codewords returned by a \(t\)-insertion (or deletion) list decoder, where \(t' < t\). Focusing on the case of \(t'=1\) and \(t=2\), we find that under two insertions, this quantity is at most \((n+12)/4\) for any VT code of length \(n\), whereas under two deletions it is at least \(n/2 - 10\) when averaged over all length-\(n\) VT codes. The nearly factor-of-two gap between these upper and lower bounds serves to confirm the relative ease of list-decoding of insertions compared to deletions from an average-case perspective.

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