Comments on: Team Continuity, Part I http://www.basketball-reference.com/blog/?p=3277 NBA & ABA Basketball Statistics & History Mon, 21 Nov 2011 20:56:04 +0000 hourly 1 https://wordpress.org/?v=4.6 By: Girls Basketball http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12093 Thu, 03 Sep 2009 23:42:21 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12093 Great article. You guys are the best

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By: Neil Paine http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12042 Tue, 01 Sep 2009 14:48:20 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12042 I see what you're saying -- perhaps I should consider low-minute guys who get a bump in PT to be newcomers instead of being in the continuity, since for all intents and purposes there's not a big difference between a young player finally getting "his turn" and someone coming to the team for the first time.

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By: Jason J http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12038 Mon, 31 Aug 2009 21:46:50 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12038 Neil - Maybe I'm misunderstanding how you've broken things down with your continuity score, but I think you might be able to take this a step farther and look more closely at minute distribution.

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.

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By: Raj http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12036 Mon, 31 Aug 2009 19:41:46 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12036 just taking a casual look at the list, in the case of a few exceptions (Min 2004 for example), most of these teams sucked.

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By: edkupfer http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12035 Mon, 31 Aug 2009 18:28:10 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12035 There is no easy way to describe it. I've tried.

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By: Neil Paine http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12034 Mon, 31 Aug 2009 18:21:28 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12034 Wow, I'm only 4 years behind you in terms of thought processes, Ed... :)

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...

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By: edkupfer http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12033 Mon, 31 Aug 2009 16:53:23 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12033

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.

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By: Ryan J. Parker http://www.basketball-reference.com/blog/?p=3277&cpage=1#comment-12032 Mon, 31 Aug 2009 16:40:14 +0000 http://www.basketball-reference.com/blog/?p=3277#comment-12032 This is why I want to use more information than just minutes played. Every year we have players change teams and/or these player's roles change, so I don't think we have to get too crazy and focus on one specific set of teams.

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.

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