# hollinger predictions - PER - ...



## windy_bull (Sep 28, 2005)

just in case you have not been laughing today - do it now :biggrin: 

http://insider.espn.go.com/nba/holl...://insider.espn.go.com/nba/hollinger/rankings


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## McBulls (Apr 28, 2005)

Guess we should have offered the money to Dan Gadzuric instead of Ben Wallace. 
Yep that PER statistic is really the thing to go by.


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## such sweet thunder (May 30, 2002)

I always feel stipid for responding to these articles; they don't deserve one. But since I have nothing better to do (and that's a reflection upon me):

31 Boozer
39 Eddy Curry
61 Gadzuric
63 Ben Wallace
64 Mike James
*77 Kirk Hinrich*
81 Jake Tsakilidis


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## ScottMay (Jun 15, 2002)

Let's take a break to hear from our sponsor:
____________________________________
John Hollinger: I'm getting a lot of question along the lines of "how do you rate so-and-so ahead of so-and-so", so I think it's time to backtrack here. 

John Hollinger: What you're seeing in the ratings are the projection for his Player Efficiency Rating for this season. PER, as I've discussed in here many times, is a summary of a player's per-minute statistical effectiveness, but that still leaves some things out -- defense, durability, etc. 

John Hollinger: A lot of people are looking at this like I'm saying Player X is better than Player Y, which isn't necessarily the case. 
____________________________________

Break over -- everyone go ahead and get back to lighting your torches and untangling your panties!


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## jbulls (Aug 31, 2005)

ScottMay said:


> Let's take a break to hear from our sponsor:
> ____________________________________
> John Hollinger: I'm getting a lot of question along the lines of "how do you rate so-and-so ahead of so-and-so", so I think it's time to backtrack here.
> 
> ...


Well, with all those caveats, what's the point of the stat? If per minute statistical effectiveness isn't a measure of a players overall worth, why bother creating a stat to measure it?


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## JeremyB0001 (Nov 17, 2003)

ScottMay said:


> Let's take a break to hear from our sponsor:
> ____________________________________
> John Hollinger: I'm getting a lot of question along the lines of "how do you rate so-and-so ahead of so-and-so", so I think it's time to backtrack here.
> 
> ...


I'm a huge fan of Hollinger but he really needs to wait to develop some sort of reliable projections before throwing his numbers out. There's obviously tons of work that needs to be with the methodology there. The fact that he openly disagrees with many of the projections does not help their credibility. I'd recommend disregarding the rankings and and reading the scouting reports if you have insider, they're pretty insightful.


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## JeremyB0001 (Nov 17, 2003)

jbulls said:


> Well, with all those caveats, what's the point of the stat? If per minute statistical effectiveness isn't a measure of a players overall worth, why bother creating a stat to measure it?


Because it creates another way to look at effectiveness, because it adds more information to the picture. Sure if the results were purely random and didn't actually measure anything it would be worthless but I'd rather have a good measure of the aspects of performance that can be measured with statistics than no measure of those skills at all. It's not pointless to know how efficiently a player rebounds just because you are not also measuring how well that player plays help defense. I guess you can quibble with the extent to which it's necessary to lump all those measurements together into PER but all encompasing measurements are sexier and it's a means of comparing the value of the multiple different skills that are measured reasonably well by stats.


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## johnston797 (May 29, 2002)

JeremyB0001 said:


> I'm a huge fan of Hollinger but he really needs to wait to develop some sort of reliable projections before throwing his numbers out. There's obviously tons of work that needs to be with the methodology there. The fact that he openly disagrees with many of the projections does not help their credibility. I'd recommend disregarding the rankings and and reading the scouting reports if you have insider, they're pretty insightful.



This is from Hollinger's chat as well...



> "Chad, Chicago: Isn't the PER stat kind of useless if it doesn't take into account defense, durability, etc. (Can you tell I've bought into Scott Skiles).
> 
> SportsNation John Hollinger: No. It sums up the "measurables" so you can move on the unmeasurables with a firmer idea of where everybody stands.


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## JeremyB0001 (Nov 17, 2003)

johnston797 said:


> This is from Hollinger's chat as well...


I missed that. It's a very good explanation of what I was trying to write in response to jbulls post.

As far as my post which you quoted, I wasn't critisizing the PER ratings which I like quite a bit but Hollinger's PER forecasts for the upcomming season. In the chat he wrote that the projections are completely objective because they are based on comparable players. I don't find that to be entirely true because the methodology used to determine which players are the most similar is going to be somewhat subjective. 

From what I can tell, Hollinger's forecasts for the upcoming season are based on the same principles as the PECOTA system developed by Nate Silver at BaseballProspectus. I know with PECOTA, the system's methodology has been repeatedly tweaked and there are studies of the systems effectiveness every season. To date I haven't seen analysis of the success and methodology of Hollinger's forecasts. 

I know from reading a lot of BP articles that Nate has found a great deal of surprising correlations between players attributes and their development (for example size plays a much bigger role than expected, the rate at which a pitcher has allowed fly balls in the previous season is a better indication of how many home runs he will give up next season than how many home runs he gave up in the previous season, etc.). I could be wrong but I suspect at this point that Hollinger is simply weighting rebound rate, size, weight, points per 40, etc. equally and finding players with the most similar numbers at a same age and then basing the projections on how those players played in the next season. In my opinion that approach leaves something to be desired.


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## such sweet thunder (May 30, 2002)

ScottMay said:


> Let's take a break to hear from our sponsor:
> ____________________________________
> John Hollinger: I'm getting a lot of question along the lines of "how do you rate so-and-so ahead of so-and-so", so I think it's time to backtrack here.
> 
> ...


That's funny,

Because this is how ESPN markets the article:

*John Hollinger ranks every NBA player from best to worst using hard facts*

To agree with jbulls (and why I'm embarassed I responded to this article in the first place):

The claim ScottMay quoted is an out -- and a weak one at that. Hollinger's job at ESPN is to make bizarre claims and then back them up with some statistical measure. He's an NBA tabloid writer, making himself the story. They market the article as a ranking system, and then he wants to go and claim they aren't necessarily how he rates players; he should at least have the balls to stand behind his methodology and make his argument.


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## Salvaged Ship (Jul 10, 2002)

See Nocioni is rated behind such powerhouses as Ryan Gomes, Tyronne Lue, Martell Webster, Jaret Jack, Maceo Basten.

Another guy who has far too much time on his hands and gets paid way to much money to produce garbage hack writing.


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## jbulls (Aug 31, 2005)

such sweet thunder said:


> That's funny,
> 
> Because this is how ESPN markets the article:
> 
> ...


Ding, ding, ding. Here's what we're getting from ESPN/Hollinger:

1. LOOK AT OUR PER RANKINGS! HERE'S WHAT GUYS ARE REALLY WORTH!

2. actual rankings.

3. (well, please understand that PER doesn't take into account a bunch of stuff that's vital in evaluating basketball players)

I love stats. I spend more time on 82games.com than I care to admit. PER is baloney. I'm sorry, but I just don't find anything worthwhile in methodology that ranks Dan Gadzuric ahead of Ben Wallace, and lists Kirk Hinrich as the 77th best player in the NBA, 4 slots ahead of the Memphis Grizzlies' backup center. It's nonsense, and the fact that Hollinger publishes these results and then somehow refuses to get behind them is just mind-blowing. Serious strides have been made in statistical analysis of basketball in recent years, and it kills me to see John Hollinger and ESPN publishing crappy nonsense fantasy basketball drivel and giving the whole thing a bad name.


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## narek (Jul 29, 2005)

jbulls said:


> I love stats. I spend more time on 82games.com than I care to admit. PER is baloney. I'm sorry, but I just don't find anything worthwhile in methodology that ranks Dan Gadzuric ahead of Ben Wallace, and lists Kirk Hinrich as the 77th best player in the NBA, 4 slots ahead of the Memphis Grizzlies' backup center. It's nonsense, and the fact that Hollinger publishes these results and then somehow refuses to get behind them is just mind-blowing. Serious strides have been made in statistical analysis of basketball in recent years, and it kills me to see John Hollinger and ESPN publishing crappy nonsense fantasy basketball drivel and giving the whole thing a bad name.


And Jackie Butler is ahead of Andrew Bogut. hehehehehe

I wish someone would talk to Pax and/or Skiles in debth about how they use stats.


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## kukoc4ever (Nov 20, 2002)

jbulls said:


> *I love stats. I spend more time on 82games.com than I care to admit. PER is baloney.* I'm sorry, but I just don't find anything worthwhile in methodology that ranks Dan Gadzuric ahead of Ben Wallace, and lists Kirk Hinrich as the 77th best player in the NBA, 4 slots ahead of the Memphis Grizzlies' backup center.


The 82games.com new lynchpin, fair salary, does not have Kirk Hinrich in the top 60.

http://www.82games.com/0506/fairsalary0506.htm

Also baloney?

What stat / methodology is not baloney?


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## ScottMay (Jun 15, 2002)

such sweet thunder said:


> That's funny,
> 
> Because this is how ESPN markets the article:
> 
> ...


I'm not sure how to respond to this. You're far, far off the mark in terms of what Hollinger's job is and what he's aiming to do with these stats. And he has no more control over what kind of headline an editor at ESPN.com slaps on his article than you or I do.

The simple fact is that the Bulls do not have a player who ranks in the top 50 (or whatever it is) in statistical production per minute. The simple fact is that Jackie Butler does produce more per minute than Andrew Bogut. Dan Gadzuric does produce more per minute than Ben Wallace. If you are making the claim that these facts aren't true, then there's no point in us discussing this any further. I'd be happy to compare interpretations of what the data means, but the data is what the data is. I tend to think it's valuable when viewed in the appropriate context.

jbulls, PER combined with on-off stuff is pretty much the bedrock of what 82games.com does. Do you take that into account when viewing their content?

narek, I wouldn't want to hazard a guess as to how much Paxskiles use stats on a day-to-day basis, but I guarantee you Pax will be bringing up Hinrich's #77 ranking the next time he sits down with Jeff Austin.

MikeDC put it best a while back -- I doubt anyone here would have been slamming PER back in the dynasty days when we had a guy all alone at the top for years and another in the top 10.


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## MikeDC (Jul 16, 2002)

such sweet thunder said:


> That's funny,
> 
> Because this is how ESPN markets the article:
> 
> ...


Thats perhaps a valid criticism for invalid reasons. The gutsy thing wouldn't be to defend his claims as legitimately measuring best-to-worst because his qualification of that is correct and I'm quite sure Hollinger believes that.

The gutsy thing would be to advertise those qualifications strongly and up front, and insist that his employer do the same, something which, as far as I can see, Hollinger has never done.

In doing so, he does a disservice to the idea of using stats in the first place, since it gives rise to stuff like this thread. Of course, it doesn't help that everyone _wants_ there to be some holy grail number that will neatly stack everyone up. That seems to lead otherwise smart people to criticise a statistic for not being something that they should know it can't be in the first place.


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## Goubot (Aug 16, 2006)

I like the PER as well, and I advise anyone who has insider to read the actual profiles instead of his predictions. The predictions are always pessimistic for everyone except the youngest players, and there's no way he can deal with things like injuries and offseason work. 

The profiles themselves are quite insightful in most cases; the guy obviously watches hundreds of games to temper his statistical analysis. As someone said, it's easy to like the stat when your players are good in it. I've seen people use it selectively to defend a favorite and dismiss it when it's used to defend someone they don't like.

The Bulls stayed above water because of defensive effort while giving a humdrum offensive showing, and offense is what the PER measures the best. The PER annually underrates Ben Wallace and players like Bruce Bowen, but Hollinger always mentions what good defenders they are in his profiles. And quite honestly, no, the Bulls did not have any offensive standouts last year, but a lot of them were above average for their position. I'm pretty sure no one complained when Hollinger predicted that the Bulls would make a deep playoff run. It's selective bias, you don't bash someone when they say something that you want to hear, but you'll discount the guy if he says something you disagree with. 

There are legitimate problems with the PER, but none of them can be seen through complaining about how Player X is better than Player Y. Also, the way ESPN is framing this is kind of silly. Hollinger's predictions for future performance are rarely right and that's how the lists are ordered.


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## Ron Cey (Dec 27, 2004)

MikeDC said:


> Of course, it doesn't help that everyone _wants_ there to be some holy grail number that will neatly stack everyone up. That seems to lead otherwise smart people to criticise a statistic for not being something that they should know it can't be in the first place.


As one who has openly criticized stats like PER and more recently Win Score, I think a point of what the criticism actually is should be made. It is not the stat itself. A statistic is an objectively accurate thing. Standing alone, as a number, it is not subject to criticism. 

*It is the use of the stat * by other fans, or anyone else, to argue that one player is better than another that is objectionable and, simply put, stupid.

If the stat is as Hollinger claims in Scott's post (though I have previously quoted Hollinger giving far more credit to the "ranking" value of his stat - he's a flip flopper on this point), and we all discuss it as a statistic with gross limitations that can't possibly be used to accurately rank actual player effectiveness, then I have absolutely no problem with it. 

I simply then come to the conclusion that jbulls does - whats the point? Well, the point is to sell John Hollinger. Which is fine. That is what ESPN and John Hollinger are supposed to do.


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## johnston797 (May 29, 2002)

MikeDC said:


> Thats perhaps a valid criticism for invalid reasons. The gutsy thing wouldn't be to defend his claims as legitimately measuring best-to-worst because his qualification of that is correct and I'm quite sure Hollinger believes that.
> 
> The gutsy thing would be to advertise those qualifications strongly and up front, and insist that his employer do the same, something which, as far as I can see, Hollinger has never done.
> 
> In doing so, he does a disservice to the idea of using stats in the first place, since it gives rise to stuff like this thread. Of course, it doesn't help that everyone _wants_ there to be some holy grail number that will neatly stack everyone up. That seems to lead otherwise smart people to criticise a statistic for not being something that they should know it can't be in the first place.


For the 4 prior seasons, Hollinger put out 4 bound, paperback editions. They are flat out excellent. He had much more control everything and quantified and "qualified" and explained the ratings in great detail. It was similar to have access to thesis-type research.

MikeDC, you were seem to be his target market. Did you ever buy his Basketball Perspective? As I recall, a year ago or so, you hadn't. Even though you were exposed to his work. Or have you bought Dean Oliver's book or any similar stat theory book?

I wish he still put out his book. His work is not as much for the stat-theory-head as it used to be. But I can't complain if they guy wants a wider audience and to make some money. IMHO, I can't see how anyone that wouldn't buy that type of work should complain.


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## Ron Cey (Dec 27, 2004)

ScottMay said:


> MikeDC *put it best * a while back -- I doubt anyone here would have been slamming PER back in the dynasty days when we had a guy all alone at the top for years and another in the top 10.


This assumes that those of us who question the meaningfulness of the stat and its use by others are just a bunch of drooling fanboys blinded by our ignorant love of the team and players we root for. This assumes that we are not capabable of objectively evaluating a statistic as it pertains to the game of basketball and then forming a legitimate opinion contrary to yours and Mike's. 

In other words, this might be the most condescending way to "put it" but it certainly isn't the best way.


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## McBulls (Apr 28, 2005)

Goubot said:


> I like the PER as well, and I advise anyone who has insider to read the actual profiles instead of his predictions. The predictions are always pessimistic for everyone except the youngest players, and there's no way he can deal with things like injuries and offseason work.
> 
> The profiles themselves are quite insightful in most cases; the guy obviously watches hundreds of games to temper his statistical analysis. As someone said, it's easy to like the stat when your players are good in it. I've seen people use it selectively to defend a favorite and dismiss it when it's used to defend someone they don't like.
> 
> ...


Ranking players numerically with an omnibus statistic is implicitly a player ranking. If Hollinger was sincerely modest about the value of the statistic he should rank order players by some other criterion, or better yet organize the discussion around a topic the statistic captures better, like "offensive effectiveness". 

When we look at a list of the top scorers in the NBA, we are not misled by what it means. We know that the players at the top of the list have coaches that let them shoot the ball a lot, and probably get lots of foul calls from the officials. Combining that list with shooting percentage tells you a lot about a player's scoring ability.

When we look at a list of the top rebounders or assist leaders, we understand what that means as well. But it's not clear what the exercise of convolving many unrelated stats together tells you. What have we learned when we find Gadzuric is ranked above Ben Wallace? That Ben is a lousy free throw shooter? Why should anyone care how the players are arranged in the list the way they are? Obviously Hollinger and ESPN care,since they wrote and published the article.


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## madvillian (Jul 13, 2006)

JeremyB0001 said:


> I missed that. It's a very good explanation of what I was trying to write in response to jbulls post.
> 
> As far as my post which you quoted, I wasn't critisizing the PER ratings which I like quite a bit but Hollinger's PER forecasts for the upcomming season. In the chat he wrote that the projections are completely objective because they are based on comparable players. I don't find that to be entirely true because the methodology used to determine which players are the most similar is going to be somewhat subjective.
> 
> ...


Cool you're a fellow saber nerd. 

I think that in general, Baseball is way ahead of Basketball in terms of statistical analysis. The new PECOTA's (this years at least) gave performance predictions based on tier's of likelyhood (by percentile) which I really liked. Plus, baseball numbers are so much more definitive than PER. A player's OPS (or whatever output stat you like, EQA I guess is the best from BP) times his PA an incredibly accurate prediction of how many wins he will contribute. In basketball PER is not nearly so certain.

I like Hollinger's efforts, but his methodology is going to have to improve.


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## johnston797 (May 29, 2002)

madvillian said:


> Cool you're a fellow saber nerd.
> 
> I think that in general, Baseball is way ahead of Basketball in terms of statistical analysis. The new PECOTA's (this years at least) gave performance predictions based on tier's of likelyhood (by percentile) which I really liked. Plus, baseball numbers are so much more definitive than PER. A player's OPS (or whatever output stat you like, EQA I guess is the best from BP) times his PA an incredibly accurate prediction of how many wins he will contribute. In basketball PER is not nearly so certain.
> 
> I like Hollinger's efforts, but his methodology is going to have to improve.


IMHO, Baseball will always be ahead of basketball because so much more of the action is captured. In baseball, every major defensive play (i.e. an out) is captured and attributed to individual players. That's can't happen objectively in basketball.

For the people that say that no statistic is valuable, that's nuts. All the NBA teams are looking at stats in great detail. Given the cutting edge of 82games and the level they have bought into Hollinger, I'd say Hollinger is a very influencial guy in the NBA. IMHO, PER is clearly the best individual statistic out there for evaluating basketball players. Sorry to the haters.


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## JeremyB0001 (Nov 17, 2003)

madvillian said:


> Cool you're a fellow saber nerd.
> 
> I think that in general, Baseball is way ahead of Basketball in terms of statistical analysis. The new PECOTA's (this years at least) gave performance predictions based on tier's of likelyhood (by percentile) which I really liked. Plus, baseball numbers are so much more definitive than PER. A player's OPS (or whatever output stat you like, EQA I guess is the best from BP) times his PA an incredibly accurate prediction of how many wins he will contribute. In basketball PER is not nearly so certain.
> 
> I like Hollinger's efforts, but his methodology is going to have to improve.


Right. I think basketball statistics - or at least the stats we have at this point in time - are much less capable of accurate describing and in turn projecting future performance so Hollinger won't be able to come up with projections like PECOTA anytime soon. I just get the impression that perhaps there is a lot more room for him to examine which statistics/factors are more predictive of future performance and which are not. More importantly, until there are some studies done to evaluate the success of the methodology he is using for the forecasts, I don't think very much emphasis should be placed on them. Certainly - and I agree ESPN takes a lot of the blame for this - players should not be ranked by the forecast when Butler takes a huge step forward and Noc regresses and no one really agrees with the underlying reasons why the system projects this (ie Noc's struggles in his first season).


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## Ron Cey (Dec 27, 2004)

johnston797 said:


> For the people that say that no statistic is valuable, that's nuts.


Who says that?


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## johnston797 (May 29, 2002)

McBulls said:


> When we look at a list of the top rebounders or assist leaders, we understand what that means as well. But it's not clear what the exercise of convolving many unrelated stats together tells you. What have we learned when we find Gadzuric is ranked above Ben Wallace? That Ben is a lousy free throw shooter? Why should anyone care how the players are arranged in the list the way they are?


To evaluate effectiveness of players across all statistical spectrums as opposed to one spectrum. Wallace isn't soley a below average offensive player due to FT%. Points/Min and Usuage are also major drawbacks.


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## johnston797 (May 29, 2002)

Ron Cey said:


> Who says that?


No need for me to do the dirty work. Let's find out. For everyone that knocks PER, what statistical evaluation is superior? 

Since no one to date in this thread has offered any alternative, I suspect some would say that "one number" evaluations are hogwash. But let's see.


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## Goubot (Aug 16, 2006)

As I said before, the PER has always underrated Ben Wallace, but Hollinger always notes what an incredible defensive presence he is. I recognize that this is a flaw of the PER, but to discount it completely would be equally foolish. The PER is valuable if used in context, the number itself doesn't tell you anything. The other stats Hollinger uses, such as Rebound Rate, Usage Rate, TS%, and Turnover Rate are all fairly good measures of a player's abilities in those categories, and those are all factored in to make the final PER. 

In a way, the PER does take into account some of Wallace's defensive accomplishments, such as his blocks and steals. But it also picks up how poor of an offensive player he is, which is how in spite of all those rebounds and defensive stats, he's just above the average. Gadzuric is an energy guy, he shoots high percentages and rebounds well without turning the ball over. He's made the best of the few minutes he's gotten. That's not to say he's better than Wallace, Hollinger himself notes that Gadzuric is slim and fouls too much, making him a question mark on the defensive end in spite of his block rate. Again, the context that you're using the PER in matters, if you just use the raw number to say that Player X is better than Player Y, that's obviously a poor use of Hollinger's statistics. If you don't delve into why a player is better or account defense into it, the stat isn't particularly useful for discussion.

It used to be that Hollinger would include Defensive PERs (which were fairly accurate, passed most of the laugh tests. For reference, Ben Wallace, Bowen and Prince were annually in the tops), which he didn't do this year. 

Another mistake that ESPN has made with this is that they've made it Insider only, so the people who question Hinrich being rated at 70 whatever only see small snippets of analysis, not the full player overviews.


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## such sweet thunder (May 30, 2002)

ScottMay said:


> I'm not sure how to respond to this. You're far, far off the mark in terms of what Hollinger's job is and what he's aiming to do with these stats. And he has no more control over what kind of headline an editor at ESPN.com slaps on his article than you or I do.
> 
> The simple fact is that the Bulls do not have a player who ranks in the top 50 (or whatever it is) in statistical production per minute. The simple fact is that Jackie Butler does produce more per minute than Andrew Bogut. Dan Gadzuric does produce more per minute than Ben Wallace. If you are making the claim that these facts aren't true, then there's no point in us discussing this any further. I'd be happy to compare interpretations of what the data means, but the data is what the data is. I tend to think it's valuable when viewed in the appropriate context.


Hollinger is not not some beat reporter desparately rushing to make deadline and get his story in to his editor, who will then slap a title on the piece that fits the page format. Hollinger is a one trick pony -- he mentions PER in every article he writes; he is essentially the basketball statistics/rankings expert for ESPN. This is his yearly moment in the sun. Are you seriously going to argue that he didn't know that ESPN would tack that headline on his article, and that he isn't better off for them doing it? It's a pure gimmick -- one that Bill Simmons could even look up to. ESPN faciliatates the gimmick. Hollinger lives off the gimmick.


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## McBulls (Apr 28, 2005)

johnston797 said:


> IMHO, Baseball will always be ahead of basketball because so much more of the action is captured. In baseball, every major defensive play (i.e. an out) is captured and attributed to individual players. That's can't happen objectively in basketball.
> 
> For the people that say that no statistic is valuable, that's nuts. All the NBA teams are looking at stats in great detail. Given the cutting edge of 82games and the level they have bought into Hollinger, I'd say Hollinger is a very influencial guy in the NBA. IMHO, PER is clearly the best individual statistic out there for evaluating basketball players. Sorry to the haters.


An omnibus statistic that has the hubris of including "performance effectiveness" in its name should be a good predictor of players relative merit in trades or selection for international teams. 
For example if PER had real merit 

Brevin Knight or Marbury, not to mention Arenas should have been a point guard on the USA team last summer.

Orlando should consider trading Dwight Howard for Carlos Boozer

LA should trade Lamar Odem for David Lee.

San Antonio should thank their stars they have Jackie Butler instead of Nene, Kristic, Ben Wallace, Brad Miller, Kamen and the other bums ranked below him.


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## such sweet thunder (May 30, 2002)

ScottMay said:


> MikeDC put it best a while back -- I doubt anyone here would have been slamming PER back in the dynasty days when we had a guy all alone at the top for years and another in the top 10.


And in response to this -- I'd bash PER regardless. It's not a good statistical measure. It's just not. And anyone who uses PER to build (and deflect) controversy in an attempt to make themselves the story, is a subpar journalist. End of story.


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## johnston797 (May 29, 2002)

Goubot said:


> It used to be that Hollinger would include Defensive PERs (which were fairly accurate, passed most of the laugh tests. For reference, Ben Wallace, Bowen and Prince were annually in the tops), which he didn't do this year.


I'm disappointed that he dropped this. Goes to my point that it's a bit dumbed down per his previous books. Also agree with the analysis that indicates the ranking should have been be last year's PER rather than the projected PER for this year.


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## johnston797 (May 29, 2002)

McBulls said:


> An omnibus statistic that has the hubris of including "performance effectiveness" in its name should be a good predictor of players relative merit in trades or selection for international teams.
> For example if PER had real merit
> 
> Brevin Knight or Marbury, not to mention Arenas should have been a point guard on the USA team last summer.
> ...


What's the value of bringing up the anomolies again? Are you saying that any existing or proposed omnibus statistic is doomed to failure? Or just Hollingers?


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## Rhyder (Jul 15, 2002)

MikeDC said:


> Thats perhaps a valid criticism for invalid reasons. The gutsy thing wouldn't be to defend his claims as legitimately measuring best-to-worst because his qualification of that is correct and I'm quite sure Hollinger believes that.
> 
> The gutsy thing would be to advertise those qualifications strongly and up front, and insist that his employer do the same, something which, as far as I can see, Hollinger has never done.
> 
> In doing so, he does a disservice to the idea of using stats in the first place, since it gives rise to stuff like this thread. Of course, it doesn't help that everyone _wants_ there to be some holy grail number that will neatly stack everyone up. That seems to lead otherwise smart people to criticise a statistic for not being something that they should know it can't be in the first place.


Fab post. I was going to say I blame the machine (ESPN), not the man.

I haven't studied Hollinger's methods, mainly because I never found it useful for my own. However, he has always seemed professional and would communicate the holes in his work.

As is the case with any statistical evaluation, you have to understand the assumptions in order to gain value from the conclusions. People as a whole like to bash stats, mainly because they are looking for something definitive (i.e. a ranking system of the best to worst players) instead of trying to understand what the stat actually means. This is why people fall in love with things like power rankings, which is really a lagging indicator, and bash things like 82games and PER, which is probably much more useful.


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## ScottMay (Jun 15, 2002)

johnston797 said:


> Given the cutting edge of 82games and the level they have bought into Hollinger, I'd say Hollinger is a very influencial guy in the NBA. IMHO, PER is clearly the best individual statistic out there for evaluating basketball players. Sorry to the haters.


At the end of the day, this is all I care about. 

Hollinger's posting regularly on APBRmetrics if anyone has a question or comment for him.


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## Ron Cey (Dec 27, 2004)

johnston797 said:


> No need for me to do the dirty work. Let's find out. For everyone that knocks PER, what statistical evaluation is superior?
> 
> Since no one to date in this thread has offered any alternative, I suspect some would say that "one number" evaluations are hogwash. But let's see.


Now you are changing it. Dramatically. You wrote that there are those who "say that no statistic is valuable". I don't think anyone believes that and I've never seen someone attempt to make that argument. Ever. 

There are many, many valuable statistics so long as the user puts them in their proper context and acknowledges their innate limitations as part of the discussion. 

Now your question is "what statistical evaluation is superior to PER?". That is totally different than accusing people of saying no statistics have value.

"One number" statistics aren't hogwash as long as they are evaluated and used correctly. Often times they are not. 

Further, saying that PER is better than other "one number stats" does not lead to the conclusion that it is good. The best of something can still be inadequate. I went to a poker party about a month ago where the host paid several strippers to attend. Evidently he was short on cash when he made his selections. It wasn't pretty. The "best" stripper there was still someone you'd rather not see naked.


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## johnston797 (May 29, 2002)

Ron Cey said:


> Now you are changing it. Dramatically. You wrote that there are those who "say that no statistic is valuable". I don't think anyone believes that and I've never seen someone attempt to make that argument. Ever.
> 
> There are many, many valuable statistics so long as the user puts them in their proper context and acknowledges their innate limitations as part of the discussion.
> 
> ...


Damn lawyers. If it makes you happier, let me amend my original comment to the following: _those who say that no *Advanced* statistic *analysis* is valuable, you are nuts._ 

Not only are you nuts. But you are outside accepted best practices in the NBA offices. Our our Dan R. is proof of this and that the stripper anlology, while fun, doesn't work.

And I think the question of "what statistical evaluation is superior to PER?" lends itself to a much better discussion than PER sucks and ,yea, why don't we trade Wallace for Butler and Hinrich for Starbury.


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## McBulls (Apr 28, 2005)

johnston797 said:


> What's the value of bringing up the anomolies again? Are you saying that any existing or proposed omnibus statistic is doomed to failure? Or just Hollingers?


Regardless of disclaimers, it looks to me that the rationale for developing PER was to develope a mathematical model that estimated the value of individual players. The test of any mathematical model is it's overall correlation with other independent measures of the issue at hand and it's ability to predict future results. In this regard outliers play a particularly important role. If an apparent outlier like Butler's rating can be explained with ease, say by the small number of minutes he played, or the quality of the opposition in the game when he played, then overall comfort with the model increases. But if apparent outliers cannot be explained, then one has to suspect that the model is flawed. 

An alternative model of player value based on salary would be a fairly independent measure that could be used to evaluate the robustness of the PER model. Salary is a numeric estimate of player value generated periodically when the player signs a contract. Players on rookie contracts can only be compared to similar players, but players with more experience can be directly compared after normalizing the time from contract signing. Of course, if GMs and agents use PER in arguments over salary, the two estimates are not entirely independent. A second limitation is that salary is a lagging indicator whose accuracy declines rapidly after the contract signing date. Nevertheless, at the time of signing salary is certainly a reasonably accurate numeric estimate of what experts in the NBA who have a real interest think a player is and will be worth. 

So how well does PER correlate with the starting years of player salary if only players who have signed a contract in the last year are included in the analysis? Or if only players in the second year of their rookie contract are included in the analysis, etc? I'm sure the different measures will be positively correlated, but a casual perusal of the rankings suggest that the correlation is probably not very high.


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## fl_flash (Aug 19, 2002)

johnston797 said:


> Damn lawyers. If it makes you happier, let me amend my original comment to the following: _those who say that no *Advanced* statistic *analysis* is valuable, you are nuts._
> 
> Not only are you nuts. But you are outside accepted best practices in the NBA offices. Our our Dan R. is proof of this and that the stripper anlology, while fun, doesn't work.
> 
> And I think the question of "what statistical evaluation is superior to PER?" lends itself to a much better discussion than PER sucks and ,yea, why don't we trade Wallace for Butler and Hinrich for Starbury.


You're simpy not getting it (and I thought the Penguin did an excellent job by the way). Maybe one more time for emphasis from a different poster: Nobody is claiming that PER or any other statistic, advanced or other, has no value. Do you understand that? Nobody.

Since you didn't like Ron's stripper analogy - try this one. Statistics - any statistic - are simply a means of measurement. Of evaluation. In the most simplistic sense, they're tools. If you want to use a phillips head screwdriver to cut some lumber, you're more than welcome to but you probably won't be too thrilled with the results. Conversely, if you choose to use your circular saw to turn a screw, you might get the job done but it sure will take you a while.

Statistics are simply a tool that is used as part of an evaluation process. Are you getting this? PART of an evaluation process. I can fully guarantee you that NBA front offices sift through and evaluate more statistical means of measurement than we are aware of. They also will use visual observation and other criteria in evaluating particular players. I'm sure PER is just part of that process - not the end-all-be-all in their decision making. If it were, there'd be a team of Jackie Butlers, Dan Gadzurics and Luke Ridinours running around being PER-riffic and winning about 10 games.

As to your query about what statistical method of evaluation is better than PER - the very basic answer is all of them and none of them. It all depends upon how their used and in what context. Much like using a phillips head screwdriver is probably best for turning a screw and a circular saw is probably best for cutting wood. PER won't tell you who the best rebounder is - Rebounds per game or Rebounds per minute might be a better statistic. PER won't tell you who the best shooter is. You might want to look at shooting percentages or maybe E-FG percentage. The examples could continue on, but I hope you get the point...

It's not the tool itself that's the problem. It's how the tool is used and in the case of PER - being propped up as this definative metric when really it's just another tool in the shed. No better or no worse than any other when used correctly.


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## JeremyB0001 (Nov 17, 2003)

such sweet thunder said:


> Hollinger is not not some beat reporter desparately rushing to make deadline and get his story in to his editor, who will then slap a title on the piece that fits the page format. Hollinger is a one trick pony -- he mentions PER in every article he writes; he is essentially the basketball statistics/rankings expert for ESPN. This is his yearly moment in the sun. Are you seriously going to argue that he didn't know that ESPN would tack that headline on his article, and that he isn't better off for them doing it? It's a pure gimmick -- one that Bill Simmons could even look up to. ESPN faciliatates the gimmick. Hollinger lives off the gimmick.


There might be some merit to your argument if Hollinger didn't write articles about offensive efficiency, defensive efficiency, rebounding rate, true shooting percentage, ussage rate, etc. and explain in detail how these statistics measure attributes that are influencing the success of teams and players.


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## Ron Cey (Dec 27, 2004)

fl_flash said:


> As to your query about what statistical method of evaluation is better than PER - the very basic answer is all of them and none of them. It all depends upon how their used and in what context. Much like using a phillips head screwdriver is probably best for turning a screw and a circular saw is probably best for cutting wood. PER won't tell you who the best rebounder is - Rebounds per game or Rebounds per minute might be a better statistic. PER won't tell you who the best shooter is. You might want to look at shooting percentages or maybe E-FG percentage. The examples could continue on, but I hope you get the point...
> 
> It's not the tool itself that's the problem. It's how the tool is used and in the case of PER - being propped up as this definative metric when really it's just another tool in the shed. No better or no worse than any other when used correctly.


Precisely. Well said.


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## johnston797 (May 29, 2002)

fl_flash said:


> You're simpy not getting it (and I thought the Penguin did an excellent job by the way). Maybe one more time for emphasis from a different poster: Nobody is claiming that PER or any other statistic, advanced or other, has no value. Do you understand that? Nobody.


Let me introduce you to this post.



such sweet thunder said:


> And in response to this -- I'd bash PER regardless. It's not a good statistical measure. It's just not. And anyone who uses PER to build (and deflect) controversy in an attempt to make themselves the story, is a subpar journalist. End of story.


This is far from the only one.


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## Ron Cey (Dec 27, 2004)

> Damn lawyers.


Right. Because precision with the written word in a forum based solely on that form of communication isn't important. 



> If it makes you happier, let me amend my original comment to the following: _those who say that no *Advanced* statistic *analysis* is valuable, you are nuts._


Who says that? 



> Not only are you nuts. But you are outside accepted best practices in the NBA offices. Our our Dan R. is proof of this and that the stripper anlology, while fun, doesn't work.


It depends entirely on usage. I WANT Paxson and Skiles to include in depth statistical analysis into their decision making processes. But I want them to do it intelligently. 



> And I think the question of "what statistical evaluation is superior to PER?" lends itself to a much better discussion than PER sucks and ,yea, why don't we trade Wallace for Butler and Hinrich for Starbury.


Well, I think the discussion is already more detailed than that.


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## johnston797 (May 29, 2002)

fl_flash said:


> As to your query about what statistical method of evaluation is better than PER - the very basic answer is all of them and none of them. It all depends upon how their used and in what context. Much like using a phillips head screwdriver is probably best for turning a screw and a circular saw is probably best for cutting wood. PER won't tell you who the best rebounder is - Rebounds per game or Rebounds per minute might be a better statistic. PER won't tell you who the best shooter is. You might want to look at shooting percentages or maybe E-FG percentage. The examples could continue on, but I hope you get the point...


As I understand the debate, I thought we were talking about the best basketball players overall. Not the best rebounders. Sorry if this is not clear to you.


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## johnston797 (May 29, 2002)

Ron Cey said:


> Who says that?


See post #42. See post #1.


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## johnston797 (May 29, 2002)

Salvaged Ship said:


> See Nocioni is rated behind such powerhouses as Ryan Gomes, Tyronne Lue, Martell Webster, Jaret Jack, Maceo Basten.
> 
> Another guy who has far too much time on his hands and gets paid way to much money to produce garbage hack writing.


Yet another example.


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## johnston797 (May 29, 2002)

McBulls said:


> Regardless of disclaimers, it looks to me that the rationale for developing PER was to develope a mathematical model that estimated the value of individual players. The test of any mathematical model is it's overall correlation with other independent measures of the issue at hand and it's ability to predict future results. In this regard outliers play a particularly important role. If an apparent outlier like Butler's rating can be explained with ease, say by the small number of minutes he played, or the quality of the opposition in the game when he played, then overall comfort with the model increases. But if apparent outliers cannot be explained, then one has to suspect that the model is flawed.
> 
> An alternative model of player value based on salary would be a fairly independent measure that could be used to evaluate the robustness of the PER model. Salary is a numeric estimate of player value generated periodically when the player signs a contract. Players on rookie contracts can only be compared to similar players, but players with more experience can be directly compared after normalizing the time from contract signing. Of course, if GMs and agents use PER in arguments over salary, the two estimates are not entirely independent. A second limitation is that salary is a lagging indicator whose accuracy declines rapidly after the contract signing date. Nevertheless, at the time of signing salary is certainly a reasonably accurate numeric estimate of what experts in the NBA who have a real interest think a player is and will be worth.
> 
> So how well does PER correlate with the starting years of player salary if only players who have signed a contract in the last year are included in the analysis? Or if only players in the second year of their rookie contract are included in the analysis, etc? I'm sure the different measures will be positively correlated, but a casual perusal of the rankings suggest that the correlation is probably not very high.



Good post. Seems like Salary is as flawed or more flawed than PER. Chandler being a good example. Ideally, i would think that you would try to rollup PER and determine if it could help you predict wins. FWIW, I think Hollinger has gone this route. Not sure how it turned out.


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## fl_flash (Aug 19, 2002)

johnston797 said:


> As I understand the debate, I thought we were talking about the best basketball players overall. Not the best rebounders. Sorry if this is not clear to you.


If you wanna get all cutsie about this - I can play that game also...

If you truly believe that PER is the best means of evaluating basketball players then all I can say to you is that you're nuts. I apologize for trying to incorporate the broader concept that PER or any other statistic is best used within the context and limitation of said statistic. Apparently that's going beyond the bounds of your thought processes. If PER is your basketball Holy Grail - more power to ya brother.

Try to wrap you mind around this one - PER is PART of evaluating the effectivness of a basketball player. As a free-standing measurement of a players overall effectivness it is sorely lacking. It has its' place in the pantheon of statistical measures. No more, no less.

The only thing I can extrapolate from your insistant postition on PER is that it is the end-all-be-all of statistical measurement and hence a team of Butlers, Gadzurics and Ridinours would run the table with ease. Whatever floats your boat Capt'n.


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## Ron Cey (Dec 27, 2004)

johnston797 said:


> As I understand the debate, I thought we were talking about the best basketball players overall.


Is that what you think PER does? Shows who the best overall basketball players are? 

Because that is the type of thinking that is at the root of my criticism of PER. The usage, not PER itself.


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## johnston797 (May 29, 2002)

fl_flash said:


> If you wanna get all cutsie about this - I can play that game also...
> 
> If you truly believe that PER is the best means of evaluating basketball players then all I can say to you is that you're nuts. I apologize for trying to incorporate the broader concept that PER or any other statistic is best used within the context and limitation of said statistic. Apparently that's going beyond the bounds of your thought processes. If PER is your basketball Holy Grail - more power to ya brother.
> 
> ...


Find where I ever said PER was the "end-all-be-all". You will not find it. In fact, I initially started posting in this thread with some of Hollinger's own disclaimers. 

The PER not garbage. It's not hack writing. It's valuable. IMHO, it's the best individual unifying stat of a player's value.


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## johnston797 (May 29, 2002)

Ron Cey said:


> Is that what you think PER does? Shows who the best overall basketball players are?
> 
> Because that is the type of thinking that is at the root of my criticism of PER. The usage, not PER itself.


Congrats, Ron. Way to pull yet another item out of context.


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## MikeDC (Jul 16, 2002)

Ron Cey said:


> This assumes that those of us who question the meaningfulness of the stat and its use by others are just a bunch of drooling fanboys blinded by our ignorant love of the team and players we root for. This assumes that we are not capabable of objectively evaluating a statistic as it pertains to the game of basketball and then forming a legitimate opinion contrary to yours and Mike's.
> 
> In other words, this might be the most condescending way to "put it" but it certainly isn't the best way.


That's not true. One could also assume those others are capable of forming a legitimate opinion but simply choose not to do so when it would be inconvenient and unpleasant. In short, they're perfectly willing to knowingly pass off BS when it's happens to be favorable.

Now see, that's way more condescending than what Scott said. More accurate as well. :clown:


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## Ron Cey (Dec 27, 2004)

johnston797 said:


> Congrats, Ron. Way to pull yet another item out of context.


I'm asking you a question. I'm not declaring that to be your position. I'm asking what your position is. Are you going to answer the very simple question? 

I personally don't understand how anyone can disagree with what fl flash is saying. In fact, based on all the well-written posts in this thread from people who both like and dislike Hollinger's work, you appear to be the only one who disagrees with fl flash. 

Almost all of the rest of us appear to be saying the same thing, just in slightly different ways: PER, and most all statistics, is useful if used properly while acknowledging its inherent limitations as part of the discussion.


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## Ron Cey (Dec 27, 2004)

MikeDC said:


> That's not true. One could also assume those others are capable of forming a legitimate opinion but simply choose not to do so when it would be inconvenient and unpleasant. In short, they're perfectly willing to knowingly pass off BS when it's happens to be favorable.
> 
> Now see, that's way more condescending than what Scott said. More accurate as well. :clown:


Yes, it is more condescending. It also accuses fraud. Well done, Mr. Administrator. You are truly above the fray. 

Perhaps you should suspend yourself?


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## fl_flash (Aug 19, 2002)

johnston797 said:


> Find where I ever said PER was the "end-all-be-all". You will not find it. In fact, I initially started posting in this thread with some of Hollinger's own disclaimers.
> 
> The PER not garbage. It's not hack writing. It's valuable. IMHO, it's the best individual unifying stat of a player's value.


Fair enough. I appreciate your claification. I would agree that PER is not garbage. I would agree that it has value. I won't go so far as to state it's the best individual unifying stat out there of a players value. Personally, I don't think there is such a metric in existance. Far too much enters into such a subjective phrase as "which player has more value". You do look at their offensive stats - and PER is as good as any in summarizing them in a somewhat cohesive and normalized fashion. After that I believe you get into a whole "beauty is in the eye of the beholder" situation. Some front offices really like Jib (for lack of a better term). That's going to weigh into their decision. How much of a raw athlete is the guy? Is he smart or stupid? There could be hundreds of other such questions/criteria that would enter into the equation and not everyone is going to ask the exact same questions.

It's like when I try to expain what a Plutonic form is to my kids. When I say the word "dog" a mental picture enters into their heads. One kid may see a german shepard. Another a beagle. The third an Akita (or whatever). It's the same with basketball players. You may see Iverson. Someone else sees Kobe or Garnett or even Gadzuric! It's at that point that PER breaks down as a means of ordering a players value. As part of determing that value - sure - PER is right in the mix. It's just I see far too many other outside variables that enter into it to have comfort stating that PER is the best one out there. In my mind, there is no "best" one; only a bunch of tools that must be used together to properly to arrive at a conclusion (that will undoubtedly be different from somone else who uses similar tools but maybe applies them differently).

I can see your position though.


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## such sweet thunder (May 30, 2002)

johnston797 said:


> Let me introduce you to this post.
> 
> And in response to this -- I'd bash PER regardless. It's not a good statistical measure. It's just not. And anyone who uses PER to build (and deflect) controversy in an attempt to make themselves the story, is a subpar journalist. End of story.
> 
> This is far from the only one.


Your taking my post out of context. When I stated, "It's not a good statistical measure" it was in reference to the number being used to show overall value. I'm attacking it's use as a gimmick to build controversy. 

My central point remains: Hollinger knows full well people are going to take the PER out of context. He conciously portrays it as measure of overall value. And then tries to backdoor out of the rediculous results, by claiming his audience is reading his articles incorrectly. Somebody make the argument that his writing -- and his role at ESPN -- aren't a gimmick. 

No one has responded to this.


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## Sir Patchwork (Jan 12, 2005)

PER is the best statistical measurement for individuals, but it's still not that accurate. I think it's valuable to use for franchise players who are all mostly in the same role, but for roleplayers, it's just not that useful. 

Basketball is still a long ways from having an end-all type stat. There is still too much going on. It's still a matter of what a player can do, versus what a player is allowed to do within the system and what his coach is asking him to do. Is what his coach is asking really the best way to use his skills? Then of course, it doesn't take into account defense, which is obviously pretty important.


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## such sweet thunder (May 30, 2002)

And now with Post # 57, I'll say it:

We're all suckers for discussing this.


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## Ron Cey (Dec 27, 2004)

Sir Patchwork said:


> Basketball is still a long ways from having an end-all type stat. There is still too much going on. It's still a matter of what a player can do, versus what a player is allowed to do within the system and what his coach is asking him to do. Is what his coach is asking really the best way to use his skills? Then of course, it doesn't take into account defense, which is obviously pretty important.


I might sound like the guy in 1927 who says we could never walk on the moon, but I simply don't think basketball is the type of game that is conducive to the development of an accurate unifying statistic in the absolute sense of ranking player quality and effectiveness. 

There are too many vital aspects of the game that are not capable of quantification and others, that while quantifiable, are misleading in what they say.


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## Ron Cey (Dec 27, 2004)

such sweet thunder said:


> And now with Post # 57, I'll say it:
> 
> We're all suckers for discussing this.


Personally, I think its fascinating. Even the 20th time around. :biggrin:


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## MikeDC (Jul 16, 2002)

McBulls said:


> Regardless of disclaimers, it looks to me that the rationale for developing PER was to develope a mathematical model that estimated the value of individual players. The test of any mathematical model is it's overall correlation with other independent measures of the issue at hand and it's ability to predict future results. In this regard outliers play a particularly important role. If an apparent outlier like Butler's rating can be explained with ease, say by the small number of minutes he played, or the quality of the opposition in the game when he played, then overall comfort with the model increases. But if apparent outliers cannot be explained, then one has to suspect that the model is flawed.
> 
> An alternative model of player value based on salary would be a fairly independent measure that could be used to evaluate the robustness of the PER model. Salary is a numeric estimate of player value generated periodically when the player signs a contract. Players on rookie contracts can only be compared to similar players, but players with more experience can be directly compared after normalizing the time from contract signing. Of course, if GMs and agents use PER in arguments over salary, the two estimates are not entirely independent. A second limitation is that salary is a lagging indicator whose accuracy declines rapidly after the contract signing date. Nevertheless, at the time of signing salary is certainly a reasonably accurate numeric estimate of what experts in the NBA who have a real interest think a player is and will be worth.
> 
> So how well does PER correlate with the starting years of player salary if only players who have signed a contract in the last year are included in the analysis? Or if only players in the second year of their rookie contract are included in the analysis, etc? I'm sure the different measures will be positively correlated, but a casual perusal of the rankings suggest that the correlation is probably not very high.


What's a high correlation in this case? I've never gotting around to asking, but you're in the social sciences, right? Think about the typical regression analysis... very often the actual R<super>2</super> sort of correlation attached to regressions is quite low and nobody bats an eyelash.

My guess though, is that you'd get a statistically signficant result, though a low R<super>2</super> if you were to regress something like T<sub>0</sub> PER against T<sub>1</sub> Salary (in which a player signs a new contract). If you introduce the very simple additional control of age, you'll get something even more significant.


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## jbulls (Aug 31, 2005)

kukoc4ever said:


> The 82games.com new lynchpin, fair salary, does not have Kirk Hinrich in the top 60.
> 
> http://www.82games.com/0506/fairsalary0506.htm
> 
> ...


I dont know. Shooting percentage? Rebounds per 48 minutes? eFG%?

If you're asking what catch-all player evaluation measure isn't baloney, I don't have an answer. I've yet to see one I'm impressed with...


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## McBulls (Apr 28, 2005)

I stated this above, but perhaps I was not clear. Salary is probably the best indicator of a player's value at the time a new contract is signed. Admittedly the figure includes not only the players present value but also an estimate of his future worth. But if one does not include rookies in the analysis the future worth component is relatively small.

Salary should reflect a players effectiveness in the year or two prior to signing his contract. Salary cap and luxury tax considerations force GMs to be careful in offering players salaries that accurately refect their current value, particularly when they are free agents. GMs who offer bad contracts lose their jobs. Organizations that offer bad contracts lose money. So these basketball experts have personal and organizational economic interest in making accurate offers.

If PER is a reasonable estimate of player value it should correlate strongly with salary, at least in contract years. But the correlation appears to be poor, even though it seems likely that PER itself is used in the contract negotiation process. Therefore PER sucks as an estimate of player value. 

To those who say it has some inherent descriptive value, I'd like to know what that is. If a player has a high PER what exactly does that mean? If he has a low PER value what does that mean? Reciting the rather arcane formula used in the model is tautological. The statistic is meant to represent something, but apparently it is not very good at it.


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## MikeDC (Jul 16, 2002)

johnston797 said:


> For the 4 prior seasons, Hollinger put out 4 bound, paperback editions. They are flat out excellent. He had much more control everything and quantified and "qualified" and explained the ratings in great detail. It was similar to have access to thesis-type research.
> 
> MikeDC, you were seem to be his target market. Did you ever buy his Basketball Perspective? As I recall, a year ago or so, you hadn't. Even though you were exposed to his work. Or have you bought Dean Oliver's book or any similar stat theory book?


I haven't... I already don't spend enough time working on the stuff I really need to work on. At this point basketball stats have been more of a hobby than a serious pursuit.


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## McBulls (Apr 28, 2005)

MikeDC said:


> What's a high correlation in this case? I've never gotting around to asking, but you're in the social sciences, right? Think about the typical regression analysis... very often the actual R<super>2</super> sort of correlation attached to regressions is quite low and nobody bats an eyelash.
> 
> My guess though, is that you'd get a statistically signficant result, though a low R<super>2</super> if you were to regress something like T<sub>0</sub> PER against T<sub>1</sub> Salary (in which a player signs a new contract). If you introduce the very simple additional control of age, you'll get something even more significant.


I'm a biologist so my standards are a bit higher than in the social sciences. Statistical significance alone is a weak argument for the robustness of the PER model; particularly since the two estimates are not independent. I would expect a decent mulitregression model of player overall performance to correlate with signing year salary in a post-hoc analysis with a correlation coefficient of at least 0.7.


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## johnston797 (May 29, 2002)

McBulls said:


> I
> If PER is a reasonable estimate of player value it should correlate strongly with salary, at least in contract years. But the correlation appears to be poor, even though it seems likely that PER itself is used in the contract negotiation process. Therefore PER sucks as an estimate of player value.


Actually, the correlation seems to be decent and many of the anomolies that Hollinger has pointed out have been on the money. He crucified GSW for the off-season where they signed guys like Murphy, Fisher and Foyle. Isiah with James. Etc.


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## MikeDC (Jul 16, 2002)

such sweet thunder said:


> Your taking my post out of context. When I stated, "It's not a good statistical measure" it was in reference to the number being used to show overall value. I'm attacking it's use as a gimmick to build controversy.
> 
> My central point remains: *Hollinger knows full well people are going to take the PER out of context.* He conciously portrays it as measure of overall value. And then tries to backdoor out of the rediculous results, by claiming his audience is reading his articles incorrectly. Somebody make the argument that his writing -- and his role at ESPN -- aren't a gimmick.
> 
> No one has responded to this.


This is a bit of a sticking point to me. Certainly Hollinger should explain how to use it (better), but it's patently silly to say he shouldn't do something for fear of being taken out of context (when it's clear that no matter what he says, he will be taken out of context by some).

It's parallel to saying, say, Stephen Hawking shouldn't try explaining string theory to a group of people who pay to see him if a substantial portion of them will walk out with a backwards notion of things. Perhaps, but that'd deny it to the portion who would get it, and that would suck.


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## MikeDC (Jul 16, 2002)

McBulls said:


> I'm a biologist so my standards are a bit higher than in the social sciences. Statistical significance alone is a weak argument for the robustness of the PER model; particularly since the two estimates are not independent. I would expect a decent mulitregression model of player overall performance to correlate with signing year salary in a post-hoc analysis with a correlation coefficient of at least 0.7.


It's not a matter of your standards being higher, it's just that in the social sciences there are lot more variables and quite a bit smaller samples


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## MikeDC (Jul 16, 2002)

McBulls said:


> I stated this above, but perhaps I was not clear. Salary is probably the best indicator of a player's value at the time a new contract is signed. Admittedly the figure includes not only the players present value but also an estimate of his future worth. But if one does not include rookies in the analysis the future worth component is relatively small.


I'd say it's even bigger... the outliers there won't be rookies but guys who are productive but aging. PJ Brown, for example, won't get a big contract next year even if he's productive.



> Salary should reflect a players effectiveness in the year or two prior to signing his contract. Salary cap and luxury tax considerations force GMs to be careful in offering players salaries that accurately refect their current value, particularly when they are free agents. GMs who offer bad contracts lose their jobs. Organizations that offer bad contracts lose money. So these basketball experts have personal and organizational economic interest in making accurate offers.
> 
> If PER is a reasonable estimate of player value it should correlate strongly with salary, at least in contract years. But the correlation appears to be poor, even though it seems likely that PER itself is used in the contract negotiation process. Therefore PER sucks as an estimate of player value.


Has someone actually done that study? I'm interested enough that I might go out and do it.

I'd also point out that although salary ought to be a good measure, it's going to be systematically flawed in several ways too. Salaries aren't linear, the bidding process is subject to the winner's curse, and there's not ideal competition in most cases.


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## such sweet thunder (May 30, 2002)

MikeDC said:


> This is a bit of a sticking point to me. Certainly Hollinger should explain how to use it (better), but it's patently silly to say he shouldn't do something for fear of being taken out of context (when it's clear that no matter what he says, he will be taken out of context by some).
> 
> It's parallel to saying, say, Stephen Hawking shouldn't try explaining string theory to a group of people who pay to see him if a substantial portion of them will walk out with a backwards notion of things. Perhaps, but that'd deny it to the portion who would get it, and that would suck.


The difference between the hypothetical and the current situation is that Hollinger is purposefully misleading his audience to raise ire, and then later claiming he was misunderstood. Stephen Hawkings, I assume, is sincerely trying to teach his concepts, not just raise controversy.


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## johnston797 (May 29, 2002)

MikeDC said:


> This is a bit of a sticking point to me. Certainly Hollinger should explain how to use it (better), but it's patently silly to say he shouldn't do something for fear of being taken out of context (when it's clear that no matter what he says, he will be taken out of context by some).
> 
> It's parallel to saying, say, Stephen Hawking shouldn't try explaining string theory to a group of people who pay to see him if a substantial portion of them will walk out with a backwards notion of things. Perhaps, but that'd deny it to the portion who would get it, and that would suck.


I had a long post to SST that gotten eaten. Some points similar to above. I also see Hollinger as more of a "one trick pony" or the designated "stat geek" at ESPN as opposed to a gimmick.

Can't fault the guy for given up some control of the content to reach a wider audience and make some more dough.


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## johnston797 (May 29, 2002)

such sweet thunder said:


> The difference between the hypothetical and the current situation is that Hollinger is purposefully misleading his audience to raise ire, and then later claiming he was misunderstood. Stephen Hawkings, I assume, is sincerely trying to teach his concepts, not just raise controversy.


Hollinger has been doing the same thing for years starting out in the wilderness. He thinks the PER has quite a bit of value in evaluating players. So thinks independent sources like 82games. Unless you have done in depth study (i.e. simply read a book of his), I fail to see how you can so completely question his motives.

EDIT p.s. I guess you could make an argument that ESPN knew that the guy's work would invite controversy and debate but it's IMHO far more grounded and a cut above than Sam Smith's weekly trade or Jay Mariotti.


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## ScottMay (Jun 15, 2002)

such sweet thunder said:


> The difference between the hypothetical and the current situation is that Hollinger is purposefully misleading his audience to raise ire, and then later claiming he was misunderstood. Stephen Hawkings, I assume, is sincerely trying to teach his concepts, not just raise controversy.


Did Hollinger run over your dog or something?

To build on what johnston said -- Hollinger developed PER *years* ago, and it became the benchmark of the basketball sabermetrics crowd long before he was hired by the Worldwide Leader.

And he wasn't hired by ESPN because of PER -- he was hired because his narrative player and team analysis is among the best in the business. As others have said on this thread, read his player capsules that accompany his predicted PER for 2006-2007. They are ridiculously in-depth and overwhelmingly right-on-the-money.

He's working for an entertainment conglomerate, not applying for foundation/grant money. I wouldn't expect him to make a life-or-death stand on PER and what it means. Similarly, I wouldn't discount the value of PER just because he "allows" his editors to build up suspense for a chat session/generate interest in his columns.


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## johnston797 (May 29, 2002)

MikeDC said:


> I'd also point out that although salary ought to be a good measure, it's going to be systematically flawed in several ways too. Salaries aren't linear, the bidding process is subject to the winner's curse, and there's not ideal competition in most cases.


I suspect that Hollinger would tell you that he developed the PER to help prove that the primarily valuation for players (i.e their salary) is flawed.

I would be interesting to see if Salaries are more correlated with PER over time. If so, that may suggest that GMs are becoming more sophisticated and using PER or something similar in recent years.


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## such sweet thunder (May 30, 2002)

ScottMay said:


> Did Hollinger run over your dog or something?


Hollinger killed Kenny. . . that *******.


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## rosenthall (Aug 1, 2002)

For what it was designed to be, I think PER is fine. For how it is sometimes utilized by ESPN as a means for a tell-all indicator of what a player is worth, its meaning is distorted and exaggerated. For the most part, I blame ESPN for that more than John Hollinger. I'm sure if one of us were to sitdown with Mr. Hollinger for an afternoon over a cup of tea, he would provide us a very lucid and articulate description of what PER can be used for, and what its limitations are, and I'm sure it wouldn't exactly correlate with how its advertised and marketed by ESPN. 

The article itself didn't really bother me too much, because I've always thought that with the way our team is designed, each players worth wouldn't be accurately captured by using just PER as a metric. We're a balanced, defense first team, that emphasizes minute and shot distribution and doesn't have much separating our first and fourth offensive option. 

If I had one beef with PER, it's that I wish John Hollinger would normalize it slightly to account for how many minutes a person plays. I realize that it has some usefulness as a per-minute-statistic, like to use it as a way to point which players should be playing more, and which should be playing less, but if that was accounted for slightly, I think it would go a long way towards a lot of the anomalies that come up in it, and we can stop reading how Mike Sweetney is the second best player on our team.


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## MikeDC (Jul 16, 2002)

McBulls said:


> I'm a biologist so my standards are a bit higher than in the social sciences. Statistical significance alone is a weak argument for the robustness of the PER model; particularly since the two estimates are not independent. I would expect a decent mulitregression model of player overall performance to correlate with signing year salary in a post-hoc analysis with a correlation coefficient of at least 0.7.


I did a really simple one by taking
1. current player contracts from Patricia Salaries (I doubled checked a couple where they weren't clear).
2. PER, age, and experience from Basketball-reference
3. A basic positional breakdown (pg, wing, forward, big guy, true center)

I haven't finished inputting the data, but I ran a quick and very simple regression on guys playing under contracts they signed in 00, 01, 02, and 03. That's only 53 guys, but it's a start. so I regressed average annual salary under the new contract against PER in the season before signing, PER in the season before that, age, experience, position dummy variables and year dummy variables (to account for changes in the salary cap, etc).

That gives an overall R Square of .663. PER in the season before immediately before signing is the only statististically significant variable, and suggests every additional point of PER is correlated with a 735k increase in average annual salary.

It may change a bit when I punch in the rest of the PERs for 04, 05, and 06, but it's a pretty strong and clear correlation.

So basically, what that's saying is that by using PER, age, experience, and position, one might reach approximately the same conclusion that the average GM makes when he's handing out a contract


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## such sweet thunder (May 30, 2002)

MikeDC said:


> I did a really simple one by taking
> 1. current player contracts from Patricia Salaries (I doubled checked a couple where they weren't clear).
> 2. PER, age, and experience from Basketball-reference
> 3. A basic positional breakdown (pg, wing, forward, big guy, true center)
> ...


 slacker.


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## McBulls (Apr 28, 2005)

MikeDC said:


> I did a really simple one by taking
> 1. current player contracts from Patricia Salaries (I doubled checked a couple where they weren't clear).
> 2. PER, age, and experience from Basketball-reference
> 3. A basic positional breakdown (pg, wing, forward, big guy, true center)
> ...


Well I thought about doing this, but I couldn't justify it in my mind (same as I couldn't bring myself to enrich ESPN by paying them to view the extended article or buying one of the books). So kudos to you. 

0.663 is a pretty good correlation, although it's not the stuff of a predictive model. Why break it down by position? If per is a valid measure of effectiveness, it shouldn't matter what position a player plays. You are definitely giving PER a break when you break the analysis down by position.

Looking at the rankings it seemed to me that the statistic worked reasonably well for shooting guards and small forwards, i.e., players whose productivity is largely defined by their ability to score. The measure seems to be not as good for point guards, and downright awful for frontline players. Does your analysis support that qualitative observation?


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## johnston797 (May 29, 2002)

McBulls said:


> 0.663 is a pretty good correlation, although it's not the stuff of a predictive model.


Again, Hollinger is modeling or predicting player effectiveness and not salary with PER. The value in PER is there is NOT necessarily a good correlation between the two.


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## McBulls (Apr 28, 2005)

johnston797 said:


> Again, Hollinger is modeling or predicting player effectiveness and not salary with PER. The value in PER is there is NOT necessarily a good correlation between the two.


And how would you evaluate the accuracy of his model? Or are you simply inclined to blindly accept whatever it poops out.


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## johnston797 (May 29, 2002)

McBulls said:


> And how would you evaluate the accuracy of his model? Or are you simply inclined to blindly accept whatever it poops out.


I've read his stuff for 5 years. He makes lots of predictions based upon his model and his scouting which I have reviewed at the time and post-facto. It passes the creditability test for me.

Hollinger passes the creditability test for 82games.com among others. His model is a core for their player valuation.

Earlier in this tread, I stated that ideally you would want to try and roll up his PER and see how it correlates with WINS not SALARY. Far better than ****ting on Hollinger's model for not correlating with salary decisions which Hollinger explicitly states are often illogical. Heck, most of Hollinger ESPN articles are about how specific individual salary and trade decisions are illogical because it doesn't correlate with PER.

No need for you to buy into PER, but it seems nonsensical to dismiss it because it doesn't correlate with Salary. It's not supposed to.


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## Ron Cey (Dec 27, 2004)

johnston797 said:


> No need for you to buy into PER, but it seems nonsensical to dismiss it because it doesn't correlate with Salary.


As much as I disregard PER as it is typically used, I agree with Johnston on this point 100%. 

Salary really isn't all that accurate a measure of effectiveness either. It is subject to the same anomolies PER is.


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## McBulls (Apr 28, 2005)

johnston797 said:


> I've read his stuff for 5 years. He makes lots of predictions based upon his model and his scouting which I have review post-facto. It passes the creditability test for me.
> 
> Hollinger passes the creditability test for 82games.com among others. His model is a core for their player valuation.
> 
> ...


The problem with using wins as an independent measure of player value is that is obviously is not as direct a measure of individual value as salary. But, if the point of the exercise is to evaluate salary decisions, then you are right, some other measure will be needed. The problem with using wins as a dependent measure is that there are so many factors that contribute to winning percentage that are not captured by existing stats. So the correlation is almost certainly going to be weak. A brief perusal of the silly wins-contributed stats on 82games adds to my suspicion that the exercise will not be enlightening.

Truth is that the less than spectacular correlation between salary and PER could be largely specious if, as seems likely, agents and NBA management have used PER in arguing the size of contracts. In effect the PER has become a bit of a self-fullfilling prophesy; i.e., players with good PER are awarded bigger contracts BECAUSE of their PER. Of course GMs like Paxson who have the good sense to pay outsized contracts to Wallace rather than Butler tend to make the correlation less than perfect. 

And the world stands in amazement when a team of players with inflated PERs is humbled by international teams containing no player who could be expected to compile a PER greater than 15.

The main fallacy of PER is that it trys to capture overall individual effectiveness in a team game whose stats are not capable of capturing important aspects of the game. Baseball and cricket are sports that lend themselves to individual statistics, since individual bowlers and batters are isolated during the game. But basketball, hockey, rugby and soccer are different animals in which teamwork, passing, team defense and other statistically invisible variables are at least as important as FG%. 

The correlation between our common sense idea of a players value and his PER is doomed to be poor at best and misleading at worst. Ranking players numerically in a list based on this statistic is stupid. Justifying the rankings with little blurbs is provocative disingenuity.


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## kukoc4ever (Nov 20, 2002)

jbulls said:


> I dont know. Shooting percentage? Rebounds per 48 minutes? eFG%?


Those are decent, but rebound rate (looks at rebounds available to collect instead of looking at it on a per minute basis) and TS% (takes into account getting to the line and competency at the line) are better.

And those are two of the main building blocks of the PER rating.

PER does not take everything that is needed to win a basketball game or be a part of a winning basketball team into account, no doubt. Its a helluva lot better than looking at PPG, RPG and ASG though. 

I like Hollinger's description of it in his chat wrap....



> No. It sums up the "measurables" so you can move on the unmeasurables with a firmer idea of where everybody stands.


After the measurables are considered..... then we can start looking at jib auras and floor burns.


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## ScottMay (Jun 15, 2002)

kukoc4ever said:


> After the measurables are considered..... then we can start looking at jib auras and floor burns.


Can you please explain how the "aura" is a better unit of measure for jib than a quotient or level?


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## kukoc4ever (Nov 20, 2002)

McBulls said:


> The main fallacy of PER is that it trys to capture overall individual effectiveness in a team game whose stats are not capable of capturing important aspects of the game.



Its not just the fallacy of PER, its the fallacy of putting any type of value into individual player statistics (PPG, RPG, ASP, SPG, BPG, FG%, FT%.... and the newer ones as well) and trying to link it to winning basketball games.

But, I'll take PER and the components that make it up (usage rate, rebound rate, assist ratio, turnover ratio, pure point ratio, ts%) over the traditional basketball stats anyday. Does the "PER is Bull" crowd grumble or gripe at the stats printed in the USA today or if someone attaches value to having a high PPG, APG, RPG?

And, if we all started a NBA basketball team today from scratch to win THIS SEASON (even if the "PER is bull" crowd was in the league), I suspect that a very high percentage of the top draft choices would just so happen to be near the top of the PER list. It does not capture EVERYTHING... but it does, IMO, capture a lot of what most knowledgeable people consider to be valuable in a good basketball player. And, it takes into account NEARLY ALL OF THE MEASUREABLES. It makes you look at the whole package (creating shots, efficiently draining buckets, grabbing rebounds, not turning it over, sharing the ball, scoring points, fouling, team pace relative to the rest of the league).


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## kukoc4ever (Nov 20, 2002)

...


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## MikeDC (Jul 16, 2002)

McBulls said:


> Well I thought about doing this, but I couldn't justify it in my mind (same as I couldn't bring myself to enrich ESPN by paying them to view the extended article or buying one of the books). So kudos to you.
> 
> 0.663 is a pretty good correlation, although it's not the stuff of a predictive model. Why break it down by position? If per is a valid measure of effectiveness, it shouldn't matter what position a player plays. You are definitely giving PER a break when you break the analysis down by position.
> 
> Looking at the rankings it seemed to me that the statistic worked reasonably well for shooting guards and small forwards, i.e., players whose productivity is largely defined by their ability to score. The measure seems to be not as good for point guards, and downright awful for frontline players. Does your analysis support that qualitative observation?


As it turns out, not much changes if I simply omit the positional variables altogether. I should have started simple first... I'm never very good at the pure math type stuff  Your R Square is still .616 if you regress salary against only PER, age, and experience, and getting rid of the extraneous stuff tightens up the result. All three variables become statistically significant.

Here's the output, by the way.



<table x:str="" style="border-collapse: collapse; width: 336pt;" border="0" cellpadding="0" cellspacing="0" width="448"><col style="width: 48pt;" span="7" width="64"> <tbody><tr style="height: 12.75pt;" height="17"> <td colspan="2" style="height: 12.75pt; width: 96pt;" height="17" width="128">SUMMARY OUTPUT</td> <td style="width: 48pt;" width="64">
</td> <td style="width: 48pt;" width="64">
</td> <td style="width: 48pt;" width="64">
</td> <td style="width: 48pt;" width="64">
</td> <td style="width: 48pt;" width="64">
</td> </tr> <tr style="height: 13.5pt;" height="18"> <td style="height: 13.5pt;" height="18">
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td colspan="2" class="xl24" style="height: 12.75pt;" align="center" height="17">Regression Statistics</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Multiple R</td> <td x:num="0.78511775507166293" align="right">0.785118</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">R Square</td> <td x:num="0.61640988932876772" align="right">0.61641</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Adjusted R Square</td> <td x:num="0.59292478051216158" align="right">0.592925</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Standard Error</td> <td x:num="2.9731059962528197" align="right">2.973106</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl22" style="height: 13.5pt;" height="18">Observations</td> <td class="xl22" x:num="" align="right">53</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 13.5pt;" height="18"> <td style="height: 13.5pt;" height="18">ANOVA</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl23" style="height: 12.75pt;" height="17"></td> <td class="xl23">df</td> <td class="xl23">SS</td> <td class="xl23">MS</td> <td class="xl23">F</td> <td class="xl23">Significance F</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Regression</td> <td x:num="" align="right">3</td> <td x:num="696.01574028838809" align="right">696.0157</td> <td x:num="232.00524676279602" align="right">232.0052</td> <td x:num="26.246839822726791" align="right">26.24684</td> <td x:num="2.8740227254738923E-10" align="right">2.87E-10</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Residual</td> <td x:num="" align="right">49</td> <td x:num="433.12860398276911" align="right">433.1286</td> <td x:num="8.8393592649544708" align="right">8.839359</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl22" style="height: 13.5pt;" height="18">Total</td> <td class="xl22" x:num="" align="right">52</td> <td class="xl22" x:num="1129.1443442711573" align="right">1129.144</td> <td class="xl22"></td> <td class="xl22"></td> <td class="xl22"></td> <td>
</td> </tr> <tr style="height: 13.5pt;" height="18"> <td style="height: 13.5pt;" height="18">
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> <td>
</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl23" style="height: 12.75pt;" height="17"></td> <td class="xl23">Coefficients</td> <td class="xl23">Standard Error</td> <td class="xl23">t Stat</td> <td class="xl23">P-value</td> <td class="xl23">Lower 95%</td> <td class="xl23">Upper 95%</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl25" style="height: 12.75pt;" height="17">Intercept</td> <td class="xl25" x:num="6.4078109847798839" align="right">6.407811</td> <td class="xl25" x:num="7.0663956792279148" align="right">7.066396</td> <td class="xl25" x:num="0.90680047872439706" align="right">0.9068</td> <td x:num="0.36895021468778522" align="right"> 0.36895</td> <td x:num="-7.7926425207802499" align="right">-7.79264</td> <td x:num="20.608264490340019" align="right"> 20.60826</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl25" style="height: 12.75pt;" height="17">PER-0</td> <td class="xl25" x:num="0.83616953847755449" align="right">0.83617</td> <td class="xl25" x:num="0.13856924822566527" align="right"> 0.138569</td> <td class="xl25" x:num="6.0343081108141741" align="right"> 6.034308</td> <td x:num="2.0721961494580165E-7" align="right"> 2.07E-07</td> <td x:num="0.55770421385480717" align="right">0.557704</td> <td x:num="1.1146348631003018" align="right">1.114635</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl25" style="height: 12.75pt;" height="17">Age</td> <td class="xl25" x:num="-0.63138300782025003" align="right">-0.63138</td> <td class="xl25" x:num="0.27400574099024055" align="right">0.274006</td> <td class="xl25" x:num="-2.3042692665433546" align="right">-2.30427</td> <td x:num="2.5487267937176601E-2" align="right">0.025487</td> <td x:num="-1.1820181493856032" align="right">-1.18202</td> <td x:num="-8.0747866254896827E-2" align="right">-0.08075</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl26" style="height: 13.5pt;" height="18">Exp</td> <td class="xl26" x:num="0.85174086330044008" align="right">0.851741</td> <td class="xl26" x:num="0.33206726717819152" align="right">0.332067</td> <td class="xl26" x:num="2.5649648354030181" align="right">2.564965</td> <td class="xl22" x:num="1.3432001709948776E-2" align="right">0.013432</td> <td class="xl22" x:num="0.18442671867309779" align="right">0.184427</td> <td class="xl22" x:num="1.5190550079277823" align="right">1.519055</td> </tr> </tbody></table>


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## johnston797 (May 29, 2002)

McBulls said:


> The main fallacy of PER is that it trys to capture overall individual effectiveness in a team game whose stats are not capable of capturing important aspects of the game. Baseball and cricket are sports that lend themselves to individual statistics, since individual bowlers and batters are isolated during the game. But basketball, hockey, rugby and soccer are different animals in which teamwork, passing, team defense and other statistically invisible variables are at least as important as FG%.


So because baskeball is more difficult to statistically model than baseball, just forget it? 



McBulls said:


> The correlation between our common sense idea of a players value and his PER is doomed to be poor at best and misleading at worst. Ranking players numerically in a list based on this statistic is stupid. Justifying the rankings with little blurbs is provocative disingenuity.


Pretty strong conclusion from someone who has admittedly not read any of the underlying equations that comprise the PER and I assume has not spent any time researching the field of advanced basketball statistics.


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## McBulls (Apr 28, 2005)

MikeDC said:


> As it turns out, not much changes if I simply omit the positional variables altogether. I should have started simple first... I'm never very good at the pure math type stuff  Your R Square is still .616 if you regress salary against only PER, age, and experience, and getting rid of the extraneous stuff tightens up the result. All three variables become statistically significant.



My first question is how did you get the table to look so nice? Surely you didn't type all the arcane 1980s style formatting commands in your post. What's the secret?

A model that describes data with an R2 of 0.6 is considered weak at best in my field. In fact, I have a rule of thumb not to worry my readers with any model that fails to describe the data with an R2 less than 0.7. Too much variance unaccounted for. The weakness becomes apparent when you try to compare alternative models with similar correlations and wide confidence intervals. No way to make an confident choice between them.


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## MikeDC (Jul 16, 2002)

McBulls said:


> My first question is how did you get the table to look so nice? Surely you didn't type all the arcane 1980s style formatting commands in your post. What's the secret?
> 
> A model that describes data with an R2 of 0.6 is considered weak at best in my field. In fact, I have a rule of thumb not to worry my readers with any model that fails to describe the data with an R2 less than 0.7. Too much variance unaccounted for. The weakness becomes apparent when you try to compare alternative models with similar correlations and wide confidence intervals. No way to make an confident choice between them.


Just pasted it straight in from Excel... sometimes it works.

I can see how that'd work in biology, but in the social sciences that just doesn't work. To be technical, of course, we could overspecify a model and inflate the R2, but in a social science setting, you've got lots of human variables and you're typically happy if you can limit things to, and find good systematic predictors.


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## Babble-On (Sep 28, 2005)

kukoc4ever said:


> And, if we all started a NBA basketball team today from scratch to win THIS SEASON (even if the "PER is bull" crowd was in the league), I suspect that a very high percentage of the top draft choices would just so happen to be near the top of the PER list.


Maybe the top 10-15 would hold somewhat to that, but even in that small percentage of the league's players, I'd think many people would think things were off, seeing as how Tim Duncan isn't even in the top 15, whereas he would be in the top 5 at least in a real draft. And when you get outide the top 15, the list is really screwy. Jackie Butler> Dwight Howard?

I think there is a lot of good stat work that goes into PER, like rebound rate and true shooting percentage, but trying to distill it all into one catch all number kinda fouls it up. I think stats are most useful evaluate them in context with a player's role on his team, the system he plays in, the players he has around him, etc. PER doesn't really seem to allow for such contextual analysis in my opinion. 


Thats why I couldn't see myself finding a use for PER if I were a GM. It seems like a shortcut. If I were looking into whether or not I wanted to sign or trade for a player, I'm not gonna look at a single number, I'm looking at all the numbers individually and putting them into context gained by observing the games. I see it as maybe something us fanboys can use for a quick reference on a player we haven't had the chance to see.


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## MikeDC (Jul 16, 2002)

I had time this afternoon to add the summer 2004 contract data and that bolsters the results a fair amount. My guess is that as we keep adding observations, we'll get a stronger result. Unfortunately, with a new baby due on Tuesday and my family coming to town, I probably won't get the last couple of years filled out in the next week or two 

<table x:str="" style="border-collapse: collapse; width: 432pt;" border="0" cellpadding="0" cellspacing="0" width="576"><col style="width: 48pt;" span="9" width="64"> <tbody><tr style="height: 12.75pt;" height="17"> <td colspan="2" style="height: 12.75pt; width: 96pt;" height="17" width="128">SUMMARY OUTPUT</td> <td style="width: 48pt;" width="64">
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td colspan="2" class="xl26" style="height: 12.75pt;" align="center" height="17">Regression Statistics</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Multiple R</td> <td x:num="0.82061444547921925" align="right">0.820614</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">*R Square*</td> <td x:num="0.67340806812916643" align="right">*0.673408*</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">*Adjusted R Square*</td> <td x:num="0.66370731767755753" align="right">*0.663707*</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Standard Error</td> <td x:num="2.6438386017066331" align="right">2.643839</td> <td>
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</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl24" style="height: 13.5pt;" height="18">Observations</td> <td class="xl24" x:num="" align="right">105</td> <td>
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</td> </tr> <tr style="height: 13.5pt;" height="18"> <td style="height: 13.5pt;" height="18">ANOVA</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl25" style="height: 12.75pt;" height="17"> </td> <td class="xl25">df</td> <td class="xl25">SS</td> <td class="xl25">MS</td> <td class="xl25">F</td> <td class="xl25">Significance F</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Regression</td> <td x:num="" align="right">3</td> <td x:num="1455.6739695102481" align="right">1455.674</td> <td x:num="485.22465650341604" align="right">485.2247</td> <td x:num="69.418141564241381" align="right">69.41814</td> <td x:num="1.9087536564629222E-24" align="right">1.91E-24</td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Residual</td> <td x:num="" align="right">101</td> <td x:num="705.9781377392826" align="right">705.9781</td> <td x:num="6.9898825518740848" align="right">6.989883</td> <td>
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</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl24" style="height: 13.5pt;" height="18">Total</td> <td class="xl24" x:num="" align="right">104</td> <td class="xl24" x:num="2161.6521072495307" align="right">2161.652</td> <td class="xl24"> </td> <td class="xl24"> </td> <td class="xl24"> </td> <td>
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</td> </tr> <tr style="height: 12.75pt;" height="17"> <td class="xl25" style="height: 12.75pt;" height="17"> </td> <td class="xl25">Coefficients</td> <td class="xl25">Standard Error</td> <td class="xl25">t Stat</td> <td class="xl25">P-value</td> <td class="xl25">Lower 95%</td> <td class="xl25">Upper 95%</td> <td class="xl25">Lower 95.0%</td> <td class="xl25">Upper 95.0%</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Intercept</td> <td x:num="9.2831562914932277" align="right">9.283156</td> <td x:num="4.3243109826053585" align="right">4.324311</td> <td x:num="2.1467365156749687" align="right">2.146737</td> <td x:num="3.4208334626693544E-2" align="right">0.034208</td> <td x:num="0.70488675847507487" align="right">0.704887</td> <td x:num="17.861425824511379" align="right">17.86143</td> <td x:num="0.70488675847507487" align="right">0.704887</td> <td x:num="17.861425824511379" align="right">17.86143</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">PER-0</td> <td x:num="0.79323659053669304" align="right">0.793237</td> <td x:num="7.5354037071100569E-2" align="right">0.075354</td> <td x:num="10.52679619259459" align="right">10.5268</td> <td x:num="6.2115334385282669E-18" align="right">6.21E-18</td> <td x:num="0.64375445500177642" align="right">0.643754</td> <td x:num="0.94271872607160967" align="right">0.942719</td> <td x:num="0.64375445500177642" align="right">0.643754</td> <td x:num="0.94271872607160967" align="right">0.942719</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">Age</td> <td x:num="-0.72820458659397014" align="right">-0.7282</td> <td x:num="0.17315308035757268" align="right">0.173153</td> <td x:num="-4.2055537509940857" align="right">-4.20555</td> <td x:num="5.6436466998341208E-5" align="right">5.64E-05</td> <td x:num="-1.0716937111630587" align="right">-1.07169</td> <td x:num="-0.38471546202488155" align="right">-0.38472</td> <td x:num="-1.0716937111630587" align="right">-1.07169</td> <td x:num="-0.38471546202488155" align="right">-0.38472</td> </tr> <tr style="height: 13.5pt;" height="18"> <td class="xl24" style="height: 13.5pt;" height="18">Exp</td> <td class="xl24" x:num="0.92227063829383493" align="right">0.922271</td> <td class="xl24" x:num="0.20179705872275161" align="right">0.201797</td> <td class="xl24" x:num="4.5702878135649136" align="right">4.570288</td> <td class="xl24" x:num="1.3822161245493248E-5" align="right">1.38E-05</td> <td class="xl24" x:num="0.52195956731459159" align="right">0.52196</td> <td class="xl24" x:num="1.3225817092730783" align="right">1.322582</td> <td class="xl24" x:num="0.52195956731459159" align="right">0.52196</td> <td class="xl24" x:num="1.3225817092730783" align="right">1.322582</td> </tr> <tr style="height: 12.75pt;" height="17"> <td style="height: 12.75pt;" height="17">
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## JeremyB0001 (Nov 17, 2003)

Babble-On said:


> And when you get outide the top 15, the list is really screwy. Jackie Butler> Dwight Howard?


Just to clarify, Butler ranking ahead of Howard is a function of the system Hollinger has developed to project players' performance for the upcomming season and not of PER as a measurement of past play. Howard (19.37) murdered Butler (14.79) in PER last season. The projections have Howard regressing by 1.97 points in PER while Butler projects to improve by 3.47 points in PER. I assure you that Hollinger does not actually expect Butler to outplay Howard this season which I find to be a very good argument in favor of scrapping this projection system until the methodology is vastly improved. As long as this discussion continues to focus on PER's effectiveness in measuring past performance, a list of the most highly rated players in PER last season is far more relevant.


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