Re: New file uploaded to APBR_analysis
- I agree. In your example, it's unlikely that Stoudamire became a much
worse player after he joined the Blazers. His change in role
contributed to the changes in his stats. In addition to this, I think
under-utilization of Stoudamire also significantly accounts for the
--- In APBR_analysis@y..., "harlanzo" <harlanzo@y...> wrote:
> I've already commented on this issue and I already agree with much
> what has been said about the econometric NBA paper. Still, I have
> been thinking about this a lot and I wondered why exactly (besides
> the conclusion of the paper) it rubbed me the wrong way. The
> reasoning that was stated (you can't have a team of iversons or a
> team of rodmans) strikes me as correct. If I was to try to further
> explain this to the author of the piece I think it boils down to
> idea that Teams as a whole have the same goal: score more points
> the other team. To get to this we can view the teams aggregate
> and compare them with each other because, in the aggregate the team
> stats are focused on accomplishing this goal.
> If you view an entire teams stats as a large pie and then look at
> individual players as contributing slices to such a pie it becomes
> evident why this model and many linear weight models are limited.
> Each player's slice in pie is accomplished because he is assigned
> with a role (ie scorer, passer, rebounder, secondary offensive
> option, not to mention defensive roles). The hope is that a player
> will help the team outscore another team and the strength of that
> player in his role enables other players to succeed (or fail) in
> their roles. So Rodman cannot just rebound and not handle the ball
> or shoot unless Jordan scores prolifically. So it really is tough
> compare a primary scorer with a guy in the Rodman/Outlaw role.
> At this point, one might argue that we can compare players of
> roles. This is true but still the problem with this is that
> roles are not fixed or static and the scorer/passer on the bulls is
> similar to the scorer/boarded on the jazz in role but not as much
> statistically. So, in some senses they are the same but in some
> are different and difficult to compare.
> Another problem is that players often shift roles. This can
> statistical analysis but it does give us a hint that some "role-
> based" evaluation is the starting point for analysis. For example,
> everyone remembers what a hot commodity Stoudamire was when he
> came to the NBA as a primary scoring option. The second he was
> traded and became a passer on portland he stock dropped. In 97-98,
> when stoudamire was traded, he went from scoring 19.5 ppg and 8.1
> with Tor to 12.4 ppg and 8.2 apg. It is unlikely that Stoudamire
> lost so much ability in half of a year. We understand, rather,
> Stoudamire's role changed.
> The question than becomes is Stoudamire more valuable as a passer
> a solid portland team or as the main scorer and passer on a crappy
> toronto team? In this sense, the I liked the econometric paper
> because it links effectiveness to wins created. Still it lacked
> ability to neogtiate that fact that there are few common
> denominantors or fixed variables in basketball stats (assuming such
> stats as they presently exist even encompass enough of a player's
> I think the starting point for the analysis is understanding which
> players are capable of (1) performing the most vital roles and (2)
> performing the most amount of roles. The more roles one player can
> fill effectively the more he frees up his teammates to do. I would
> propose that to study players we identify all the roles we can
> up (offensively and defensively) where possible and then view how
> teams perform with such players in the roles versus when they have
> other players.
> A good example of this looking at the point guard/initiators of the
> Lakers of 90-91 and 91-92. This is when, I'm sure you recall,
> retired and was replaced with Sedalle Threatt. The two teams are
> nearly identical (most key players and the coaches were the same).
> The one major differnece was trading Magic for Threatt at the
> point. Just looking at the stats, Magic is superior to Threatt:
> ppg apg rpg
> Magic 19.4 12.5 7.0
> Threatt 15.1 7.2 3.1
> But how this superiority reflects in wins is the real question.
> Apparently Magic is worth 15 more wins than Threatt (58 to 43). I
> not sure how to work back stastically to make it jive with this
> result but this I think might be the best way to analyze players.
> Anyway, I've babbled along long enough but to sum up I agree with
> what most everyone else has said. I just think this role stuff
> reflects the way NBA players function.
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File : /Warriors Stats.pdf
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Description : Analysis of the Golden State Warriors 2004-05 Season
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