Right now if I understand right your continuity % considers any player who was a member of the team the previous year to be in continuity - meaning his role won't change dramatically, but I'd say a player who gets a significant boost in minutes (due to trading / retiring of a star or natural progression or whatever) could also be considered as new to the team for your purposes. So I guess looking at the backups of lost players who aren't clearly replaced might be a way to gauge this when you calculate continuity rather than just who is new to the lineup and who isn't.

I'm thinking of a guy like Terrell Brandon, who didn't join the Cavs between '94 and '95 but went from starting 10 games to 41 games because of Mark Price's injuries. Even Drexler was buried behind All-Star Jim Paxson as a rookie (don't think he started even 10) and came on as a completely new player his sophomore year.

The denominator is minutes by the players on Team A in year Y-1 (essentially 48*5*82, plus OT minutes). The numerator is minutes by those same players, logged while playing for Team A in year Y.

So, for example: 2005 Orlando Magic continuity % = (minutes by members of '04 Magic playing for Orlando in 2005) / (total minutes of Magic roster in 2004).

Yeah, that was probably a horrible explanation that made it even more confusing...

the % of team minutes being filled by players who were on the roster the season before

Can you explain precisely what is in the numerator and denominator? Me and Dean Oliver use two different versions of what I call "Roster Stability" (see this post and Dean's reply), but this is something that has always interested me.

My goal is to build models that analyze a specific set of players on the court at one time and approximate things like shot distribution, rebounding rates, etc. Only time will tell if doing this is an improvement over a simple method, but I agree with the points you make about roles and how we might best predict players put into new roles.