That’s a broad question. If you’re comparing to Score, then you lose Participation and Immunity from Irrelevant Alternatives, as with other Condorcet methods. You also don’t satisfy Later-no-harm, very important to RCV folks, and Later-no-help, which confers robust burial resistance. But RSSM is still fairly resistant to burial and has simple anti-chicken-dilemma strategies, more so than other Condorcet completion methods.
The real question is, what are you trying to solve for in a single winner election? My goal is to find the candidate closest to the centroid of the sentiment distribution, with a method that resists strategic voting to encourage sincere expression. RSSM does that as well as anything else I’ve seen, with the ease-of-use of Score.
It seems to me that STAR is also trying to find the centroid winner, but can fail sometimes owing to its lack of clone-independence. STAR advocates argue that their failures are not failures. But if you can’t pass a basic Yee picture test, which is a very low bar for centroid approximation, then you aren’t going to find the centroid winner in general use.
As stated in the Approval Sorted Margins page, Sorted Margins yields the pairwise ordering that does the minimal damage to the underlying seed ranking. Also see the definition of a Marginal Defeat. The Sorted Margins winner has no marginal defeats.
I just added an example to the repo of the 2013 Minneapolis Mayoral election. Since RCV doesn’t translate exactly to Score, I approximated it by giving first choice 5 points, 2nd choice 4 points, and 3rd choice 3 points. RSSMQRV gives the same winner and runner-up result as RCV for that election. You can run it using
./rssmqrv.py -vv -t 1 -i examples/actual-mayoral-election.csv | less
(Edit: also RSSM does indeed satisfy the expanded Condorcet criterion that if a candidate is not defeated by any other candidate, they are the winner. Such a CW might tie another candidate, but that other candidate would have a pairwise defeat to another candidate.)