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Brian M
Joined: 25 Nov 2006
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PostPosted: Wed Apr 04, 2007 10:22 am Post subject: Interpreting adjusted plus/minus Reply with quote
I've been thinking about adjusted plus/minus lately. The big appeal to adjusted +/- is that it gives you an idea of how effective a player has been once you control for outside influences (a player's sub, the lineups he typically plays in, etc) that impinge on the unadjusted +/-.
However, it occurs to me that there is a limit to the extent to which adjusted +/- is really context free. Whenever we are able to control for factor X in a player's raw +/-, we are able to control for it because we can estimate the effect of X by comparing data from when X is present to data when X is absent. From this it follows that we can only control for those factors that are alternatively present and absent over the course of a season.
Now, there may be factors that have non-trivial effects on a player's effectiveness that are never really "off" over the course of a season. The most obvious example is the effect of a coach (assuming he is not fired midseason) and whatever offensive and defensive systems he favors.
There is also the possibility that roster effects like this may exist. For instance, suppose for the sake of argument that Steve Nash's impact on the effectiveness of his team's play is greater when he happens to be playing with lithe, athletic frontcourt players rather than lumbering, bruising frontcourt players. (One could also imagine guards that might be more effective with the bruisers.) If Nash were on a team where some of the regular frontcourt players were lumbering and others were lithe, we would be able to control for this effect to some extent. But if Nash were on a team where all his frontcourt players were of one type or the other, we would not.
More generally, whenever a player's effectiveness might be affected by the nature of the players around him, our ability to control for these effects are limited by the range of players that are actually on his team. So for instance, although we can control for the effects of the other Suns players on Nash's +/-, there is still a sense in which Nash's adjusted +/- is specific to the roster he happens to be a part of. Again, for the sake of argument, assume Nash is better off playing with lithe, athletic frontcourt players. Then put Nash on a team of slow bruisers and, all else being equal, his adjusted +/- will be worse than it is on the Suns.
So, it seems that adjusted +/- can never really give us a completely context-free sense of how effective a player is. Rather, they can give us a sense of how effective he is in a context where some set of factors (e.g. coaching, perhaps type of teammate, etc.) is held constant.
Perhaps that's all old news, in which case I would appreciate references to older discussions on the topic. Or perhaps my arguments are flawed or need qualifications in which case comments are welcome.
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Dan Rosenbaum
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PostPosted: Wed Apr 04, 2007 12:24 pm Post subject: Reply with quote
I certainly don't disagree with these observations, but we could say the same things about box score stats. We likely also could say the same thing of subjective evaluations. What I think this says more than anything is that extrapolating from the past to predict the future get more difficult as the context changes more signficantly.
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DLew
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PostPosted: Wed Apr 04, 2007 3:36 pm Post subject: Reply with quote
I view adjusted plus-minus statistics as the best measure we have of how good a player was, adjusted for the factors that we can adjust for (teammates, opponents, homecourt advantage). Now, sometime you don't want to know how good a player was, but instead how good he will be. If you want to know how good someone will be it makes sense to me to use how good they were as a starting point and then make adjustments to that based on what factors changed (age, teammates, coach, etc.).
Adjusted plus-minus tells you some things about a player, and it can serve as a useful starting point for determining other stuff that you want to know.
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Mark
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PostPosted: Wed Apr 04, 2007 4:32 pm Post subject: Reply with quote
Adjusted +/- does seem a valuable companion to the set of boxscore based information. Adjusted 4 factor analysis would seem to extend the usefulness. Is there any reason to believe or suspect that Dallas and Winston/Sagarin take this path and consider it a key part of their self-perceived edge on the competition?
Has anyone taken league distributions of pts, minutes, salaries and compared (or plotted) them with counterpart PER and adjusted +/- distributions?
If salary were based heavily or soley on adjusted +/- would they become more unequal than today? Looking beyond rookie contracts, on average do stars return surplus value (according to adjusted +/-) over cost or proportional? For what it is worth the top 25 highest paid guys playing average +5 to 6.
After the top 1/3rd of the talent pool does the question shift from returning positive value to minimizing any harm? Does such a change make a difference or is it just word substitution?
After your top 4 differencemakers should guys close to neutral on 4 factors for position be bid up instead of shopping for rotation guys with 1 strength (and a salary based on the strength) and then trying to offset any weaknesses? Do the better teams do the former more often than others do? Does Dallas? I guess it depends on how balanced and strong your top 4 are on the 4 factors. I can see adding a specialist to nudge team stats on a 4 factor needing assistance or to maintain a style of play that depends on a 4 factor strength from the bench like with the starter. But if the top 4 is strong and balanced, maybe neutral is pretty good from there (and possibly cheaper).
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Brian M
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PostPosted: Thu Apr 05, 2007 1:02 pm Post subject: Reply with quote
Thanks for the responses. I have another question: from a purely mathematical standpoint, is it possible that all the players on a given team might have a negative (or positive) adjusted plus/minus? Or is it the case that even with adjustments from the regression, some constraints necessitate that at least some players will show up with a positive (or negative) adjusted +/- to counterbalance that of their teammates? (I would imagine the answer is that it is indeed possible for an entire roster to be positive or negative on adjusted +/-.)
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DLew
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PostPosted: Thu Apr 05, 2007 2:42 pm Post subject: Reply with quote
It is definitely possible for an entire team to be negative or positive if the team was that bad/good and all the players on the team were of similar quality. It doesn't happen in real life though, because every team bad team has an above average player and every good team has a below average one.
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gabefarkas
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PostPosted: Fri Apr 13, 2007 12:28 pm Post subject: Reply with quote
Mark wrote:
Adjusted +/- does seem a valuable companion to the set of boxscore based information. Adjusted 4 factor analysis would seem to extend the usefulness. Is there any reason to believe or suspect that Dallas and Winston/Sagarin take this path and consider it a key part of their self-perceived edge on the competition?
Can you explain what you're thinking when you say "adjusted 4 factor analysis"? I'm curious what you would use to adjust them.
Mark wrote:
If salary were based heavily or soley on adjusted +/- would they become more unequal than today? Looking beyond rookie contracts, on average do stars return surplus value (according to adjusted +/-) over cost or proportional? For what it is worth the top 25 highest paid guys playing average +5 to 6.
After the top 1/3rd of the talent pool does the question shift from returning positive value to minimizing any harm? Does such a change make a difference or is it just word substitution?
I would think that's a bigger difference than you are making it out to be. What's the average point differential per game? For the 05-06 season, the Pistons had the best record in the league, and their difference in points scored to points allowed was (96.8 - 90.2 = ) 6.6 ppg. For the Spurs, who had the next best record, it was (95.6 - 88.8 = ) 6.8 ppg. On the other end of the spectrum, the Blazers averaged (88.8 - 98.3 = ) -9.5 ppg, and the Knicks (95.6 - 102.0 = ) -6.4 ppg. If one of your top 25 guys plays 36 mpg, he's affecting the outcome of the game by 3 or 4 points per contest. That seems to me like he could impact the W's and L's.
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HoopStudies
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PostPosted: Fri Apr 13, 2007 12:51 pm Post subject: Reply with quote
gabefarkas wrote:
Mark wrote:
If salary were based heavily or soley on adjusted +/- would they become more unequal than today? Looking beyond rookie contracts, on average do stars return surplus value (according to adjusted +/-) over cost or proportional? For what it is worth the top 25 highest paid guys playing average +5 to 6.
After the top 1/3rd of the talent pool does the question shift from returning positive value to minimizing any harm? Does such a change make a difference or is it just word substitution?
I would think that's a bigger difference than you are making it out to be. What's the average point differential per game? For the 05-06 season, the Pistons had the best record in the league, and their difference in points scored to points allowed was (96.8 - 90.2 = ) 6.6 ppg. For the Spurs, who had the next best record, it was (95.6 - 88.8 = ) 6.8 ppg. On the other end of the spectrum, the Blazers averaged (88.8 - 98.3 = ) -9.5 ppg, and the Knicks (95.6 - 102.0 = ) -6.4 ppg. If one of your top 25 guys plays 36 mpg, he's affecting the outcome of the game by 3 or 4 points per contest. That seems to me like he could impact the W's and L's.
Reality checks on the range of point (or win) value of players is useful. I'm not thinking about individual specific values, but what should be the range from best to worst? Is there a good way to step back and say that the best player should be n pts/game (or per 48 minutes or per something else) better than the worst? Usually this is a good exercise and reasonably simple because you don't have to identify who exactly or what exactly is best/worst.
It is also important to put things on the same scale. For instance, DLew's piece on adj+/- http://82games.com/lewin2.htm suggests that the range of marginal contribution to the team's pts/100 possessions is nearly 40 pts. (20 for Dirk, -18 for Rip) That's essentially, but not the same as the "per contest" basis you cite. (Note that 3-4 pts/contest is very different than 40.) I believe -- correct me if I'm wrong -- that DLew's stuff is per team 100 possessions, not individual 100 possessions. In other words, it's a marginal contribution to the team's 100 poss.
I think this would be a good thing to have some general consensus on...
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Mark
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PostPosted: Fri Apr 13, 2007 4:40 pm Post subject: Reply with quote
Gabe, what I was thinking in general when I said "adjusted 4 factor analysis" was to use exactly the same methodology used for adjusted team +/- as a whole- the main adjustment being the presence of the other 9 players on the court who might be above average, near average or below average on each of the 4 factors on offensive side of the ball or defensive which affects the floor context and should affect the evaluation of the players 4 factors "results".
Unless anyone sees a reason that it is not appropriate or feasible. I would think it is, as team +/- is essentially the weighted product of the 4 factors after all. Turnovers and offensive rebounding seem straightforward. FT/FG might seem mainly individual but probably is affected by good passers, outsider shooters and maybe post scorers. If there are postive and negative impacts of teammates on others FG%s then the standard adjusted method should find it just as it finds impacts at the team +/- rollup level.
As for impact, the top 25 paid players averaging a +5-6 per 100 possessions impact on adjusted team +/- does seem pretty big and differencemaking. I asked a question about value and later tacked on a finding about impact but rather than saying I underestimated impact (though I started with a somewhat skeptical tone) I think it would be more accurate to say that I havent fully processed the surplus or proportionate value to cost argument. But it could be done if you found the average salary for a neutral adjusted +/- player (something that seems very worth doiing and different than "replacement level player" or average or median paid player) and plotted average adjusted + /- vs average salary.
In relation to the scale issue Dean is right that the top players will look more impressive measuring from the very top to very bottom rather than just to the neutral on team +/- player. who (just guessing here) may indeed be an above the median performer.
Last edited by Mark on Sat Apr 14, 2007 2:59 pm; edited 3 times in total
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Mark
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PostPosted: Fri Apr 13, 2007 5:14 pm Post subject: Reply with quote
In the frontiers of apbrmetrics thread I sketched out that you could try to split and find adjusted scores for players on the 4 factors offensive and defensive for them personally as well as other team plays while they were on the court where they werent not directly the leading actor but may have had a secondary role and deserve some of that credit.
But there would be methodological hurdles to overcome on the local splits.Scoring local results 100% based on boxscore matchup might be a simplistic starting point but you could do better. Ideally you'd want to go off videotape. Short of that you'd estimate off an intelligent matchup system from play by play logs as 82games does or could estimate using Mike G's starter/sub ratio based on minutes played method. And instead of assuming the local result is 100% based on the counterpart stat matchup you could blend in team offensive and defensive strength as part of weight/ real world influence for each 4 factor activity as you estimate is appropriate.
It may have been dense to read and too far flung but I went on to suggest that ultimately you might try to know not only average rates and adjusted impacts for these 16 splits of the 4 factors but also to try to find marginal 4 factor rates and adjusted marginal impacts perhaps off of game by game logs from where they exceed their average minutes or in the especially important case of shooting when they exceeded their average shots (though you could measure marginal rates at any point of their total history curve)
If you got thru these first 2 levels of analysis then I speculated you could try to build demographic based 4 factor production functions.If you did all that then it would seem you would have a pretty complete multi-level 4 factor model and database that you could continue to refine and query and project or simulate off of. Perhaps directly using calculus to move between levels of functions (or implictly) and game theory to try to address team and player matchups and so on. On a professional basis (for team, academia or as a book writer) or perhaps on a community project basis this seems doable with current methods and alot of effort. I don't know how far it will be pursued (or has already been privately) but I welcome any feedback on the sketch of this framework. At a minimum when I think about the frontier that is what came to mind.
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gabefarkas
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PostPosted: Fri Apr 13, 2007 8:22 pm Post subject: Reply with quote
Mark wrote:
Gabe what I was thinking in general when I said "adjusted 4 factor analysis" was to use exactly the same methodology used for adjusted team +/- as a whole- the main adjustment being the presence of the other 9 players on the court who might be above average, near average or below average on each of the 4 factors on offensive side of the ball or defensive which affects the floor context and should affect the evaluation of the players 4 factors "results".
So can you sketch out what you would envision as a hypothetical result of this analysis? Would it be something like:
Code:
On/Off eFG% OR% FT/FG TOr
Player X +2.2 +1.2 -1.5 -1.2
Player Y -1.7 -0.2 +0.2 -2.2
where a possible interpretation would be be that Player X is a sharpshooting, good offensive rebounder, while Player Y doesn't do much on the offensive end, but is smart with the ball and doesn't turn it over very much?
Mark wrote:
In relation to the scale issue Dean is right that the top players will look more impressive measuring from the very top to very bottom rather than just to the neutral on team +/- player. who (just guessing here) may indeed be an above the median performer.
I would think that the exact average player's +/- would invariably be 0, no?
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Mark
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PostPosted: Fri Apr 13, 2007 8:38 pm Post subject: Reply with quote
I think you could use adjusted 4 factor analysis to say such things as Player X is a differencemaking sharpshooter if his adjusted FG% scored showed that or a differencemaking offensive rebounder if the adjusted scored showed that. Sticking with team 4 factor level data and impacts. If you did the personal / non-personal team split I've mentioned you coulod further identify the direct portion of the total effect and the indirect portion and the split may vary by player and situation and it may be worth knowing this split detail.
With regard to this question:
[Mark] "In relation to the scale issue Dean is right that the top players will look more impressive measuring from the very top to very bottom rather than just to the neutral on team +/- player. who (just guessing here) may indeed be an above the median performer."
[Gabe] "I would think that the exact average player's +/- would invariably be 0, no?"
I dont think it is invariable that average (mean or median) would be O on the adjusted scale, just that the score would be the weighted average adjusted score or the 50% percentile adjusted score. The adjusted scale is, I believe, court impact based not zero based on average player. I mistated that two posts above and may have mislead you into this and corected it so as to not misguide others. I do not know if the "average" player is neutral, positive or negative at 4 factor scores. What would be invariable, if I am thinking about it correctly, is that the sum of all the player's adjusted scores minute weighted for any of these 4 factors would balance back to zero but the distribution is unknown, could be heavily affected by top players offsetting the majority.
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Mark
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PostPosted: Fri Apr 13, 2007 9:03 pm Post subject: Reply with quote
Further brainstorming on the kinds of questions that adjusted 4 factor analysis could pursue:
1. Aggregrating data across the league do 40% 3pt shooters have a bigger impact than 35% 3 pt shooters? How much more? Is it sensible? How should it affect market salaries or coaching strategy?
2. Do 20 pt a game players who have some minimum level of "post play" have the large impact on team FG% that conventional wisdom credits them with?
3. How does the average benefit of above average penetrators compare to strong 3 pt shooters and post players? Does position appear to matter with this comparison?
4. If you had adjusted offensive rebounding impacts scores could you then look at breakouts of 5 man lineups and look at average scores for various C/PF combos of stout 7 footers, skinny 7 footers, quick hop sub 7 footers and burly sub 7 footers and decide how you want to run your rotation or shop in the summer?
5. Can you use the adjusted team (nonpersonal) split of adjusted offensive rebounding to identify or confirm the presence and impact of the guy who boxes out really well, beyond what the eye or unadjusted team on/off data shows?
6. Can you use the adjusted team (nonpersonal) split of adjusted turnovers rate to identify or confirm the presence and impact of the guy who contributes to teammates making fewer or more turnovers (apart from his own personal turnover rate and an improvement over the information contained in unadjusted team turnover rate on court that doesnt apportion out shares of responsibility) ?
7. Is the impact of a player that draws foulshots frequently better understood as the sum of his own activity and perhaps a positive impact on foulshots earned by others? In another case, alternatively, you could find a guy that draws a lot of personal fouls but when he passes leaves his teammates heaving last second outside shots and not getting as many foulshots as they normally would playing with others and find that split information diminishes the value of the initial player's activity and somewhat gives the other players an excuse for their shortfall.
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Mark
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PostPosted: Fri Apr 13, 2007 11:25 pm Post subject: Reply with quote
HoopStudies wrote:
Reality checks on the range of point (or win) value of players is useful. I'm not thinking about individual specific values, but what should be the range from best to worst? Is there a good way to step back and say that the best player should be n pts/game (or per 48 minutes or per something else) better than the worst? Usually this is a good exercise and reasonably simple because you don't have to identify who exactly or what exactly is best/worst.
It is also important to put things on the same scale. For instance, DLew's piece on adj+/- http://82games.com/lewin2.htm suggests that the range of marginal contribution to the team's pts/100 possessions is nearly 40 pts. (20 for Dirk, -18 for Rip)
...
I think this would be a good thing to have some general consensus on...
40 points seems fairly reasonable for the top to bottom spread for a season (setting aside whether Rip deserved his rating as you suggest). I would think it would have to be at least 30 points and considering offense and defense impacts (local and spinoff impact elsewhere) and the extreme pairs of strengths and weaknesses on these maybe the absolute top to the absolute bottom could even be 50 points or more. If you imposed a minimum on minutes it might improve the bottom case and cut the differential some.
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gabefarkas
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PostPosted: Sat Apr 14, 2007 12:03 am Post subject: Reply with quote
Mark wrote:
I think you could use adjusted 4 factor analysis to say such things as Player X is a differencemaking sharpshooter if his adjusted FG% scored showed that or a differencemaking offensive rebounder if the adjusted scored showed that. Sticking with team 4 factor level data and impacts. If you did the personal / non-personal team split I've mentioned you coulod further identify the direct portion of the total effect and the indirect portion and the split may vary by player and situation and it may be worth knowing this split detail.
I don't think it's that simple. I recall reading about (and doing) analyses about Iverson a few years ago where even though his eFG% was somewhere in the .435 - .450 range, and well below the team average, the team shot better overall when he was on the court. Heuristically, I attribute it to his ability to draw defenders and "create" easy shots for his teammates. It's very hard to quantify though.
Mark wrote:
With regard to this question:
[Mark] "In relation to the scale issue Dean is right that the top players will look more impressive measuring from the very top to very bottom rather than just to the neutral on team +/- player. who (just guessing here) may indeed be an above the median performer."
[Gabe] "I would think that the exact average player's +/- would invariably be 0, no?"
I dont think it is invariable that average (mean or median) would be O on the adjusted scale, just that the score would be the weighted average adjusted score or the 50% percentile adjusted score. The adjusted scale is, I believe, court impact based not zero based on average player. I mistated that two posts above and may have mislead you into this and corected it so as to not misguide others. I do not know if the "average" player is neutral, positive or negative at 4 factor scores. What would be invariable, if I am thinking about it correctly, is that the sum of all the player's adjusted scores minute weighted for any of these 4 factors would balance back to zero but the distribution is unknown, could be heavily affected by top players offsetting the majority.
Well, for the league as a whole, teams scored on average 7955 points during the 05-06 season, and allowed on average (wouldn't you know it) 7955 points for the season. That would imply, to me at least, that on average a team's +/- would be 0.0, no? Am I missing something?
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Mark
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PostPosted: Sat Apr 14, 2007 12:36 am Post subject: Reply with quote
On your first point of your post, I am in fact suggesting that using the adjusted method applied to eFG% or perhaps rolled up with freethrows to form TS% and isolated to the nonpersonal portion only might be the best way to try to quantify the much discussed "shot creation value" for players.
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Chronz1
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PostPosted: Sat Apr 14, 2007 4:35 am Post subject: Reply with quote
Before I read this post I just want to ask, where do we find these adjusted data? Seriously been bugging me, I knew the limits of raw numbers ever since I saw how ridiculously low some stars were. Yao Ming being an example in 03-04 on a 50 win team. The numbers just never added up but I knew it had to do with the quality of the opposition on the floor and Houstons rotation.
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HoopStudies
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PostPosted: Sat Apr 14, 2007 10:07 am Post subject: Reply with quote
Mark wrote:
40 points seems fairly reasonable for the top to bottom spread for a season (setting aside whether Rip deserved his rating as you suggest). I would think it would have to be at least 30 points and considering offense and defense impacts (local and spinoff impact elsewhere) and the extreme pairs of strengths and weaknesses on these maybe the absolute top to the absolute bottom could even be 50 points or more. If you imposed a minimum on minutes it might improve the bottom case and cut the differential some.
The point is not what "seems" anything. I think there is a way to do a pretty strong analysis of what the range should be, independent of an adj +/- analysis or Wins Created or whatever.
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Mark
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PostPosted: Sat Apr 14, 2007 1:37 pm Post subject: Reply with quote
I was indicating relative comfort with the existing range found by the adjusted method. If you say "I think there is a way to do a pretty strong analysis of what the range should be, independent of an adj +/- analysis or Wins Created or whatever", then it would help if could you sketch out your idea further. I couldnt see where you were going with it, that is different than everything out there.
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Mark
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PostPosted: Sat Apr 14, 2007 1:44 pm Post subject: Reply with quote
Chronz do you know about the adjusted work here?
http://www.82games.com/articles.htm
This is the resource library for now. David Lewin's articles were a welcome addition to the public domain. Basketballvalue may add adjusted resources in near future.
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Chronz1
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PostPosted: Sun Apr 15, 2007 4:12 am Post subject: Reply with quote
Mark wrote:
Chronz do you know about the adjusted work here?
http://www.82games.com/articles.htm
This is the resource library for now. David Lewin's articles were a welcome addition to the public domain. Basketballvalue may add adjusted resources in near future.
Never seen that page actually, thanks Ill get started to see if that helps me better understand these numbers.
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HoopStudies
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PostPosted: Sun Apr 15, 2007 10:30 am Post subject: Reply with quote
Mark wrote:
I was indicating relative comfort with the existing range found by the adjusted method. If you say "I think there is a way to do a pretty strong analysis of what the range should be, independent of an adj +/- analysis or Wins Created or whatever", then it would help if could you sketch out your idea further. I couldnt see where you were going with it, that is different than everything out there.
I put the idea out because I haven't developed a way of doing it. I just know it's a standard scientific practice and that someone should be able to do this... No time for me to really think about it these days.
(And I would say that a range of 40 seems too large to me.)
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Mark
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PostPosted: Sun Apr 15, 2007 12:47 pm Post subject: Reply with quote
The range shown by adjusted method is player isolated to an extent but it is still player often in a set role and in a system under a coach that is a winning environment or not. The underlying skill differences may not be near as wide as the productivity / impact demonstrated. Maybe only half as wide or less? Take low impact players and give them a better role or environment and I think many of them could lift their adjusted rating.
Sorting the adjusted values reported by David Lewin I see 57% of all players within +5 to -5. 32% are 5-10 points higher or lower than neutral. 11% have values 10+ points from neutral. 89% within a range of 20. 25% within +2 to -2.
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Mountain
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PostPosted: Mon Dec 17, 2007 9:43 pm Post subject: Reply with quote
Brian M
PostPosted: Thu Apr 05, 2007 11:02 am
"Thanks for the responses. I have another question: from a purely mathematical standpoint, is it possible that all the players on a given team might have a negative (or positive) adjusted plus/minus? Or is it the case that even with adjustments from the regression, some constraints necessitate that at least some players will show up with a positive (or negative) adjusted +/- to counterbalance that of their teammates? (I would imagine the answer is that it is indeed possible for an entire roster to be positive or negative on adjusted +/-.)"
DLew
PostPosted: Thu Apr 05, 2007 12:42 pm
"It is definitely possible for an entire team to be negative or positive if the team was that bad/good and all the players on the team were of similar quality. It doesn't happen in real life though, because every team bad team has an above average player and every good team has a below average one."
I've wondered about something similar to Brian M's question as well. Virtually every team will have an above average and below average player relative to the players on that team but is it less certain that every team will have a well above average and well below average player on adjusted +/- relative to performance of the larger population of players in the league?
Looking at 2005-6 study at 82 games every team but one had a better than +4 guy and a worse than -4 guy and the exception didnt have a -4 or worse guy. Of 30 team tops and bottoms (60 count) there are 55 held by greater than +6 or a less than -6 guys. In 04-05 it was 50 and a couple near misses. It is really consistent and makes me wonder a little. The tops and bottom player ratings are fairly similar on 60% to 2/3rds of the teams too in the respective seasons. Maybe it is all true and I thought it may be worth asking this question again. Is there any area of doubt where the methodology might be scaling based on teammates comparisons too much or stretching the rating each way too much or not giving enough weight to how they compare to rest of league?
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Dan Rosenbaum
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PostPosted: Mon Dec 17, 2007 11:57 pm Post subject: Reply with quote
With standard errors in the range of 3 to 5, we would expected to see adjusted plus/minus ratings with ranges from 12 to 20. Because of that variation it is not surprising to see quite a bit of variation on any given team.
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Mountain
Joined: 13 Mar 2007
Posts: 1527
PostPosted: Tue Dec 18, 2007 2:15 am Post subject: Reply with quote
A range of 12 on any given team is not surprising. A range of at least 12 total up and down from zero on almost 90% of the teams... is that surprising or expected? It depends in part on more precisely what the average standard error is but it is probably expected. Top and bottom individual talent is distributed thru the league by impact of salary cap, draft, etc.
In 05-06 2/3rds of teams have at least 2 greater than +6 guys. Less than half have 3. Only 2 had more than 3 - that seems light but that is the report. (One team lost in first round of playoffs- the Kings- and the other was much praised for breadth of talent Finals runnerup Detroit.)
Of the 5 teams who won 1/3rd of games or less 3 of the 5 had 3 guys at +6 or better, one had 1 and the last had none.
Maybe this pattern is worthwhile to note in itself. It is in rough agreement with conventional wisdom about a super 2 or a big 3.
I wonder how closely the share of point differential big 3's are responsible for according to adjusted +/- is to agreement with Berri's finding / promotion of the Pareto principle with respect to player contributions to wins using Wins Produced method in various articles? Mike G published his big 3 shares by eWins. Wonder how the big 3 share looks in other methods.
Last edited by Mountain on Wed Dec 19, 2007 12:53 am; edited 1 time in total
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Harold Almonte
Joined: 04 Aug 2006
Posts: 616
PostPosted: Tue Dec 18, 2007 8:18 am Post subject: Reply with quote
+/- needs a "player role adjust" in every play, but that means to use what the metric is avoiding: stats and action weighting
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Mountain
Joined: 13 Mar 2007
Posts: 1527
PostPosted: Tue Dec 18, 2007 8:21 pm Post subject: Reply with quote
The problem of a player being on court with a notable someone else heavily thus giving high influence to what happens when each is off the court (and perhaps stretching the difference for the two players) was addressed with Richard Hamilton / Ben Wallace and Jamison / Arenas cases in 05-06 article. Major cases like this may be rare but another one maybe Gooden on court with James 90% of time and off court results appear to matter a great deal as there is a 32 point difference in their overall ratings. Together and not together are integral for this method and most cases probably yield accurate results but this was part of the basis for my return to the topic briefly. Perhaps there are more cases with milder off court effects that perhaps color a little too much?
The degree of year to year stability of adjusted +/- ratings with trades or major team changes is a large topic with a number of issues but if it is not particular stong (going off memory that is not) you can come back to the question of whether teammate affects are somehow overemphasized and performance measurement and rating relative to the rest of league is not quite getting accomplished as precisely as desired. But my caution is from a general, limited outside perspective and not from a qualified technical nuts & bolts review. An attempt to give the authors feedback in case they find something within it worth checking further or others doing or study adjusted +/- deeply.
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Mountain
Joined: 13 Mar 2007
Posts: 1527
PostPosted: Thu Dec 20, 2007 12:53 am Post subject: Reply with quote
This is pure adjusted +/-.
Cautions have been raised about it of many occasions. The noisiness of the ratings was acknowledged in the orginal presentation. I see cases of best players on weak teams that don't feel "right" and cases of players of good teams that are probably better in the abstract or compared to rest of league who may suffer a bit in the context of their strongest teammates and an overall strong team.
Overall +/- (with statistical +/- as the dominant partner) was created to go beyond pure +/- and its issues. It is of more interest but not currently blended and presented. I hope the newer publishers of pure adjusted +/- ratings will consider going on to some form of overall +/- with direct credit for individual actions while on court.
Adjusted +/- split into the 4 factors would be another helpful direction to get a better feel what is happening within the roll-up +/-.
Pardon the repeat. I'll probably let it be from here..