The Strengths and Limitations of "Advanced Basketball Statistics"
Frank Herbert's masterpiece Dune series features many themes involving politics, religion and ecology/scarcity of resources but Herbert's biggest message is that it is extremely dangerous for any society to elevate one person to hero or messiah status; Paul Muad'Dib's holy war overthrew the repressive regime of the Padishah Emperor Shaddam Corrino IV but then Muad'Dib's followers--blinded with messianic dreams of his supposed infallibility and drunk with their newfound power--brought forth their own brand of tyranny. What does this have to do with basketball? There is no doubt that scouting methods and player evaluation techniques in the NBA have been improved over the past few decades and that they can and should continue to be improved. Four decades ago, the expansion Cleveland Cavaliers built their roster in no small part by relying on statistics found on the back of basketball cards; obviously, that is not a very effective scouting method or even a very effective use of basketball statistics. Within the past two decades, technology has transformed NBA scouting and game preparation and executives/coaches now have access to a proliferation of statistical information that would have been impossible to gather and organize before. I am not opposed to the use of statistics--or even "advanced basketball statistics"--to evaluate basketball players individually or collectively. I am opposed to any form of thought or analysis that lacks rigor, logic and consistency. I am opposed to theories that are presented as definitive fact without any testable hypotheses. In short, I am opposed to the way that some "stat gurus" are trying to replace previous player evaluation methods with some kind of blind, unquestioning certainty that anything that appears in a spreadsheet must be treated as holy gospel: these "stat gurus" are overthrowing the "Padishah Emperor" only to go on a holy war to wipe out any beliefs about basketball that do not rigidly conform with what appears on their spreadsheets."Advanced basketball statistics" can be useful as a supplement to traditional box score data and to the observations of trained scouts/coaches--but some "stat gurus" (and their media sycophants) do a disservice to their cause by overstating the meaning and reliability of their data (I suspect that legitimate researchers into basketball statistics cringe every time they read one of Henry Abbott's biased, tendentious rants). Published reports indicate that the 2011 NBA champion Dallas Mavericks used data from Roland Beech about the effectiveness of various lineup combinations to help decide how to allocate minutes during their playoff run; plus/minus numbers and adjusted plus/minus numbers for various lineups can be useful information for a coach to consider, provided that the data is from a large enough sample size and that there is some other corroborating information--such as observations about mismatches generated by certain lineups--that confirm what the data suggests. In Dallas' case, plus/minus information apparently confirmed what could also be seen visually: Dallas' playoff opponents had trouble matching up with J.J. Barea's speed and quickness. However, that data neither proved nor disproved that Barea is an All-Star caliber player or even that he is a better overall player than the players whose minutes he took; the data merely suggested that, paired with four other particular Dallas players, Barea helped Dallas to exploit certain matchup advantages against various lineups being used by opposing teams.
The problem--the tipping point where the necessary revolution overthrowing the old Emperor transforms into a bloody holy war--is when "stat gurus" who have proprietary numbers that they have created and used to sell books/articles start loudly and repeatedly proclaiming that they can precisely rank every individual player in the NBA and that their rankings are absolutely correct and completely objective while all other rankings (including those by other competing "stat gurus") are the products of sheer ignorance. Scientists who are conducting legitimate research consistently use cautious, guarded language, while "stat gurus" are often bombastic and tend to make wild, unverifiable claims about the accuracy of their formulas; Albert Einstein's theories led to the creation of technological marvels ranging from the atom bomb to GPS and yet researchers are still running experiments to verify his predictions. In contrast, many "stat gurus" devise their own personal interpretations of which box score numbers are most important in order to create "advanced basketball statistics" that have no designated margin for error and no framework providing ways to prove or disprove their validity. How naive do you have to be to think that a basketball player's value can absolutely and precisely be calculated to the tenth or hundredth of a point? You would think that these "stat gurus" would be concerned about the demonstrated fallibility of boxscore numbers but far too many "stat gurus" close their eyes and pretend that the basic assist, steal and blocked shot numbers that they plug into their precious "advanced" formulas are completely accurate.
The basketball "stat gurus" are trying to follow in the footsteps of Bill James and the other baseball numbers crunchers who have transformed our understanding of that sport but basketball and baseball are fundamentally different games from an analytical standpoint; it would perhaps be only a slight exaggeration to say that baseball is like checkers while basketball is like chess: computers have "solved" checkers but, even though computers have become quite proficient at playing chess, computers have not come close to "solving" chess. Similarly, baseball's number crunchers have made some valuable observations about how to properly analyze that sport but basketball's "stat gurus" are lagging far behind because their task is much more complicated: baseball consists of discrete actions that can be accurately separated and measured--pitcher throws the ball, batter hits the ball, fielder catches the ball, etc.--while basketball consists of 10 players simultaneously doing a variety of things, many of which cannot be measured.
Phil Birnbaum has worked extensively with baseball statistics but after thoroughly studying "advanced basketball statistics" he concluded that they are not particularly reliable:
You know all those player evaluation statistics in basketball, like "Wins Produced," "Player Evaluation Rating," and so forth? I don't think they work. I've been thinking about it, and I don't think I trust any of them enough put much faith in their results.
That's the opposite of how I feel about baseball. For baseball, if the sportswriter consensus is that player A is an excellent offensive player, but it turns out his OPS is a mediocre .700, I'm going to trust OPS. But, for basketball, if the sportswriters say a guy's good, but his "Wins Produced" is just average, I might be inclined to trust the sportswriters.
I don't think the stats work well enough to be useful.
Nick Collison is a perfect example of what Birnbaum is talking about. Collison is a plus/minus superstar but does that mean that he is an All-Star or All-NBA caliber player? No, but it could mean any number of other things:
1) Collison very effectively fills a limited role on a team that has two All-NBA players (Kevin Durant and Russell Westbrook) plus a third high quality player (James Harden) who provide scoring and shot creation.
2) Collison is much more effective than other players on his team who play his position, so when he enters the game his team does better than it does with him off of the court.
3) Collison is not better than the other power forwards on his team but he has more of a matchup advantage against the reserve players he competes against than other Thunder power forwards have against the opposing power forwards who they face.
4) Collision's gaudy plus/minus numbers merely reflect a lot of noise due to an insufficiently large sample size of minutes.
For the Oklahoma City Thunder, all that matters is that lineups that include Collison are very productive; "advanced basketball statistics" can be helpful for the Thunder in terms of identifying that trend and thus confirming what the coaching staff likely already had figured out by watching the games--but "stat gurus" or media members who try to extend the use of plus/minus data from one tool that can help the coaching staff to configure a playing rotation to some kind of absolute player rating system are asking far more of the data that it can rightfully be expected to provide. Plus/minus data can be noisy and is much more applicable within a team setting than applied on a league basis; at best, Collison's numbers just suggest that he can be an effective member of certain five man rotations for the Thunder--but those numbers do not prove that he is a better player than a power forward on a different team who has lower plus/minus numbers.
Last year I cited Ken Pomeroy's research about the limitations of plus/minus statistics; Pomeroy concluded, "It's true plus-minus captures everything that's happening, but that includes a whole lot of random things that lead to a hoop or a stop. Things that have nothing to do with the ability of the player you want to analyze. In basketball analysis, we should be filtering out randomness, not embracing it." In my article I added the following analysis:
Pomeroy notes that because the professional season is much longer than the college season there may be "limited use" for adjusted plus/minus in the NBA but even in that case one probably needs at least two full seasons of data to make any meaningful evaluations; in other words, most of the stat-based articles (about "clutch performance," player ratings, MVP rankings, etc.) that are popping up like dandelions in an untended yard are using data sets that are far too small to form the basis for sweeping, definitive conclusions (I realize that not all of these articles are using plus/minus or advanced plus/minus data but there is even less reason to trust the accuracy of Berri's numbers or Hollinger's numbers--both of which are based on subjective formulas that can be tweaked to reach whatever conclusions the author desires--then there is to trust plus/minus data that truly is objective in some sense even if it is only potentially meaningful when the data set is very large).
As Birnbaum mentioned, similar limitations apply to the seemingly endless number of highly touted player rating systems that have popped up in recent years. A recent article suggested that Kevin Garnett's value was not properly appreciated until some "stat gurus" created numbers that proved how effective he is. Kevin Garnett was drafted straight out of high school and shortly after that he received the biggest contract in NBA history at that time, a contract so huge that it helped lead to the 1999 lockout; Garnett was a highly valued commodity many years before "stat gurus" started touting his worth. More to the point, while the "stat gurus" declared that he was the best player in the NBA during the mid-2000s the reality that we have seen since the Boston Celtics formed their "Big Three" is that Garnett has a tremendous impact defensively and he is valuable as a screener/passer offensively but he and his teams are most effective when he is surrounded by multiple perimeter players who can create their own shots and create shots for others. Garnett's lone deep playoff run in Minnesota came when he teamed up with Sam Cassell and Latrell Sprewell and his playoff runs in Boston have been aided by the offensive skills of Paul Pierce, Ray Allen and Rajon Rondo. Regardless of what the "stat gurus" think that their numbers show, Garnett is not a dominant player in the same way that Shaquille O'Neal, Tim Duncan and Kobe Bryant have been dominant players for multiple championship teams--and despite having at least three future Hall of Famers, the Celtics won exactly one title since Garnett arrived and they do not seem likely to add to that total. In that same time period, Kobe Bryant won two championships paired with a player who had earned one All-Star selection (and had not won a single playoff game) prior to joining the Lakers and Dirk Nowitzki won a championship paired with an aging future Hall of Famer plus a cast of good role players--and Nowitzki's squad beat the "stat guru" dream team of LeBron James, Dwyane Wade and Chris Bosh. Before the "stat gurus" get too proud of themselves for allegedly discovering Kevin Garnett they might want to try to explain why the James-Wade combination has not been nearly as dominant as they predicted it would be.
Roland Beech has done some nice research about game-winning shots but, unfortunately, a lot of people borrow his data without bothering to consider his conclusion: "Ultimately though while this kind of thing is fun, it's not to my mind particularly meaningful, other than indicating that the league as a whole could probably get more efficient in 'end game' possessions...one easy place to start might be to try and be less predictable! It's nice to have a go-to guy, but when the other team knows without much doubt that a certain guy is getting the ball, it is going to be a lot easier to defend!" Beech is right on target that this data is both "fun" and "not...particularly meaningful" though I think that he is a bit harsh regarding the alleged lack of efficiency on "end game" possessions; he fails to consider two very important points: (1) since this is a small sample size the shooting percentages are disproportionately skewed downward by desperation heaves, broken plays, etc.; (2) it is very difficult to score against a set NBA defense and it is even more difficult to do so when your time is extremely limited, particularly if you need a three pointer just to tie. When the time is limited why would a coach design a play for someone other than his best player? Anyway, most people have no idea how plays work in the first place; no NBA coach is just giving the ball to one guy and saying, "Shoot it" (unless there is only enough time to catch and shoot): you give the ball to your best player because he is most capable of creating his own shot, creating a shot for someone else if he gets trapped and making free throws if he is fouled. You don't want to give the ball to someone who cannot dribble or who cannot get a shot off or who is a bad free throw shooter. When role players hit big shots it is usually after the team's best player created an opening--but if you give the ball to the role player first then you are asking him to do something he is not comfortable doing. If "stat gurus" think that "clutch shooting" percentages are low now just imagine what those percentages would look like if coaches started drawing up plays for non-ballhandlers to catch the ball at the top of the key with five seconds remaining.
I have consistently maintained that Being a Clutch Player is More Significant than Just Making Clutch Shots; I have never pretended to know or even care which NBA player is the best at making last second shots--but I am perplexed that so many "stat gurus" (other than Beech) think that this is an important topic to investigate ("stat gurus" famously do not believe in the so-called "hot hand" so there is no reason for them to believe that a player will perform much differently in some arbitrarily defined "clutch" moment than at any other time); I am also amazed at the lack of intellectual rigor displayed by the conclusions that have been loudly and repeatedly stated in some quarters about this issue. Setting aside for a moment the fact that "clutch shots" have not been universally defined in terms of time remaining/score differential, regardless of how such shots are categorized they comprise just a tiny, unrepresentative portion of a player's total shot attempts--and within that small subset of "clutch shots" there are in fact many different kinds of shots that cannot reasonably be lumped together. For instance, consider two "clutch shots" that Kobe Bryant recently attempted; near the end of the fourth quarter versus Detroit, Bryant received the ball outside the three point line in the top of the key area, took two strong dribbles and drained a midrange pullup jumper to send the game into overtime; near the end of overtime, with the Lakers trailing by three and the Pistons possibly ready to foul rather than permit a three point attempt, Bryant caught the ball well behind the three point line and quickly fired a shot that missed. If you are a "stat guru" measuring "clutch shots" then you lump in Bryant's desperation three pointer with his two dribble pullup, combine it with some half court shots and other miscellaneous attempts taken against a variety of defenses with differing amounts of time on the clock and then you produce one field goal percentage that supposedly provides a definitive measurement of Bryant's "clutchness." Does anyone measure the "clutchness" of NFL quarterbacks by looking at their completion percentages on "Hail Mary" passes? This stuff is so foolish that I cannot believe that it is a topic for supposedly serious discussion; the problems with sample size are so obvious that it should be readily apparent that "clutch shot" data is, at best, a fun, frivolous stat to consider lightly, and not something that is worthy of in depth debate. If someone nails a lucky half court shot does that prove that he is "clutch"? The reality is that most shots taken in the final few seconds against a set defense are inherently low percentage shots--but it should not be surprising to anyone that in the same game Bryant calmly nailed a two dribble pullup (a shot that is a normal part of his repertoire) and then missed a twisting, rushed, long three point attempt; anyone who combines those two attempts into one "clutch shooting percentage" and takes that number seriously is an idiot.
***************
Further Reading:
The Counterfeit Currency of David Berri's Wages of Wins
Economics is Not a Science, Nor is Basketball Statistical Analysis
Economics is Not a Science, Nor is Basketball Statistical Analysis, Part II
Economics is Not a Science, Nor is Basketball Statistical Analysis, Part III
The Difference Between Measuring Defense in Basketball and Baseball
Labels: "advanced basketball statistics", Frank Herbert, Henry Abbott, Ken Pomeroy, Kobe Bryant, Nick Collison, Paul Muad'Dib, Phil Birnbaum, stat gurus
posted by David Friedman @ 7:20 AM
17 Comments:
Hello David,
I am portuguese and have been reading your blog for quite a long time and enjoy it a lot. I love basketball and have loved it since the eighties, my favourite players of that time being Isiah Thomas, Magic Johnson and Michael Jordan. My favourite player for the last 15 has been Kobe Bryant, ever since i saw him first. I noticed something different about him and the way he has developed his game through the years has confirmed that. I won't go into the jordan vs Kobe thing because i find it ridiculous, they are both amazing and probably two of the most complete basketball players i have ever seen and both of them have advantages and disadvantages over each other. I pretty much agree with your thoughts on basketball most of the time, though not always but that's great, we can't all feel the same about everything, that would be pretty boring ;)
As a Laker fan, i don't know where we are going but i'm sure something has to be done in order for the lakers to be serious contenders again and not so dependent on Kobe. I don't know if the Dwight Howard trade would be the answer but i guess we'll find out during the next week. I'm in no way a Lebron hater, i find him an amazing player with a physical condition more similar to an NFL player than a NBA player, what he can do in a court is nothing short of amazing but even though he has these amazing stats he is nowhere near as complete as Kobe. There's still a lot missing but i do believe that if he wants to develop his game he will indeed be the King everybody calls him. I guess we'll see that later in his career when age catches up with him and his speed and strenght won't be the same. His lack of killer instinct is the only thing that i really don't believe he can change, he just doesn't have it whisch is trully sad because then he would be unstoppable.
Anyway, i was only making my presentation and now i'll move on the subject of your post. Statistics is a thing that me, as an european, just can't understand. I love basketball as much as i love soccer and in soccer nobody cares about statistics the way people care in american sports, not only basketball. I find it confusing that there are people that believe that games or championships can be won based on statistics rather than team play and individual moments of magic...or even luck. Anyway, just wanted to share my opinion with you and congratulate you on your blog.
Nuno Rechena
My biggest problem with those who live and die by statistics is that they completely disregard the human element of the game. Athletes are human beings, not statistics. The stats are merely a byproduct of their actions. It is very hard to predict the exact future actions of human beings, and that is why "advanced stat formulas" are inconsistent at predicting future success of teams/players. The value of a player goes way beyond PER, plus/minus, and win shares. "Stat gurus" either can't see this, or simply refuse to.
Nuno:
Thank you for your interest in my writing and for leaving such a detailed comment. I also like Isiah, Magic and MJ, though my favorite players--as you probably already know since you are a long time reader--are Julius Erving and Scottie Pippen.
I think that the only foreseeable way for the Lakers to salvage this season is to find a way to acquire Dwight Howard and then try to have an attack similar to the one developed by the '95 Rockets, with Bryant and Howard playing the roles of Drexler and Olajuwon while the other Lakers fill various, more limited roles as defenders and spot up shooters. However, it seems as if the Lakers are more interested in finding a way to deal Gasol for a legit starting pg. If the Lakers pull that off and Bynum stays healthy the Lakers may improve somewhat but not enough to overtake the Thunder or Spurs. A younger Bryant could perhaps carry this team by averaging 40 ppg for a month while shooting .480 or better from the field but Bryant has logged far too much mileage to put up those kinds of numbers for an extended period, particularly with the games scheduled so tightly together.
Michael Joseph:
I have no problem with the attempt to better quantify what happens on the basketball court through the use of statistics; my problem is with people who think that this project has already been successfully completed when it is in fact just in its infancy and it faces serious challenges due to the complex nature of the sport with 10 players acting simultaneously in ways that are not easily measured.
I should have clarified that I have no problems whatsoever with the use of advanced stats and those who utilize them, in themselves. What irks me are those individuals who fail to acknowledge the limitations of such methods. I'm not the biggest fan of John Hollinger, but I know that he does acknowledge the potential flaws of his methods, and for that I respect him. I just have a problem with those individuals who treat advanced stat formulas as some kind of exact science, especially when they pick and choose sample sizes that conveniently fit their biases and agendas. I won't name any names.
Advanced statistical analysis can be fascinating. Misuse and misinterpretation of it is absolutely infuriating, and that is why I read this blog instead of TrueHoop (or anything ESPN related), Basketbawful, Ball Don’t Lie, etc..
In other words, keep up the good work!
This entire post reads like a bit of a rant against Dave Berri, and you're not the only one. Just know two things: 1) his WP metric isn't useless by any means, and 2) most people who work with these stats aren't of Berri's attitude, and would completely agree with you that there's no such thing as the "perfect stat". So be careful not to paint stats people as the bad guys.
Just as bothersome as the guys who adhere to the "be-all, end-all" stat are the people who will deny any evidence that protrays their favorite player in a negative light. It can go both ways.
Anonymous:
If WP is not "useless" it is awfully close to "useless." When someone tells me that Rodman was better than MJ and that Gasol, Bynum, Odom and probably every other 6'10" guy in L.A. is better than Kobe that someone is either drunk, delusional or Dave Berri.
My favorite player is Dr. J and I could not care less what, if anything, Dave Berri says about Dr. J. My basketball analysis is based on skill set comparisons, not who I like/don't like.
Basing your analysis on "skill set comparison" is all well and good, but these stats deal with value and not necessarily talent/ability. There's a difference. The other thing to keep in mind is that the skill still has to translate on the court somehow. Bill Simmons once called Rasheed Wallace the most talented player in NBA history - perhaps a hyperbole to highlight his underwhelming career, but whatever unlimited talent he had didn't exactly come out on the court in production.
Also, discounting a metric because you believe it overrates particular player isn't the way to go. There are scientifically valid methods you can use to demonstrate the "usefulness" of a particular stat. WP certainly has its own biases, but it isn't useless.
Anonymous:
When I talk about skill sets I am talking about what you call "value" as opposed to theorizing about what a player could do if he fully applied himself.
I don't give any serious credence to what Bill Simmons says about basketball. He is a perfect example of what you complained about in terms of a fan overvaluing his favorite player--in Simmons' case that would be his favorite team, Boston.
Many respected "stat gurus" have given detailed explanations of the flaws in Berri's methodology and I have quoted some of those explanations in previous posts but I think that it is also useful to point out that WP simply does not pass the "eye test"--it asserts things that are ludicrous at face value. Dennis Rodman was a wonderful rebounder and defender but Horace Grant--who was a very good player but not even a HoFer--ably filled those roles on three previous championship teams and there were several other pfs who could have successfully filled those roles alongside MJ and Pippen; maybe the Bulls would not have gone 72-10 with some of those other guys but they could have still won multiple titles. MJ was clearly the best player of his era and you cannot seriously compare an all-around player with a specialist like Rodman. Berri's more recent assertions about a host of players--Bryant, Iverson, Gasol, Bynum, etc.--are equally ridiculous. I have covered these issues extensively here, so rather than reiterating those old discussions now I encourage you to do a keyword search of this site to revisit those articles and learn more about my refutations of Berri's nonsense.
I also read Simmons opinion re: Rasheed and hardly think it's outrageous or rooted in homerism (he trashed Rasheed while he was in a Boston uniform ; indeed, you'd come to similar conclusion yourself (prodded by the same statement by Charles Barkley) : http://20secondtimeout.blogspot.com/2008/01/enigmatic-rasheed-wallace.html
Matt:
I don't know or care specifically what Simmons' opinion is of Rasheed Wallace; I am speaking of the overall quality of Simmons' basketball analysis, not a handful of times that he may have accidentally made sense.
Mark Cuban said it best "anything you get from the box score is useless".
To do meaningful statistical analysis, the source stats have to be something you don't get from the box score; they're tallied in video well after the game is done. For instance for FG attempts you would distinguish where the shot was taken, what type of shot it was, how it was defended. There are many types of assists as well, and all need to be distinctly documented. And the same goes for rebounds. Even then, your analysis won't be perfect, but it's a hell of a lot better than these individual box score amalgamations people try to create. Junk in, junk out. If you refine your source data, you're going to get a better result when you analyze the numbers. Box score stats are just to "chunky". They were not meant for meaningful statistical analysis.
Gil Meriken:
Cuban's Mavs are known as a team that uses basketball statistical analysis but the Mavs use that data to assist with creating the best matchups/most effective five man lineups and not with trying to prove to two decimal points who is the best player in the NBA. Roland Beech and Wayne Winston are two "stat gurus" who have been publicly identified as consultants to the Mavs. I doubt that the Mavs put much stock into what Berri, Hollinger and other creators of individual player ratings are doing.
You quote approvingly a comment to the effect that WP and PER "are based on subjective formulas that can be tweaked to reach whatever conclusions the author desires." This does seem to be true of PER; but the formula for WP is arrived at through regression analysis. The values attributed to various box score statistics are not simply dreamt up on a whim, and to say so is just factually incorrect. You might think WP wrongly values players, but I don't see how you can claim that it's some sort of conspiracy to impugn the the career of Kobe Bryant.
Anonymous:
The technical flaws in Berri's WoW have been extensively discussed many times before, both at this site and elsewhere, so I am not interested in going back and forth with you over territory that has already been covered but as a courtesy to you (and other readers who may be unfamiliar with the technical flaws in Berri's work) here is one link that should provide answers to your questions (assuming that you are in fact seeking knowledge and not simply parroting Berri's company line like Owen and some other people like to do):
The Pot Calling the Kettle Black
David:
I am happy to have found your blog while searching for discussions on basketball lineups.
This post is of particular interest because I created an iPad/iPhone app to help coaches at all levels capture plus/minus detail and found most of the benefit came from using the lineup statistics during half-time.
While a single half is an absurd sample, we found it to be the most relevant vs. a seasons worth of data. (understandably not a decent sample size either)
Do you have any comments on the use of lineup statistics from one half of play and how they correlate to second half performance? Could the 2nd half performance correlate more to the 1st half data than to a seasons worth of results?
My observations are from prep ball where it is easier to have lineups standout, yet I am interested in your take on this matter because i have observed NBA coaches (not including Dallas) will often not play lineups in the 2nd half that were successful in the 1st half. (even if the opponent placed the same lineups on the floor that were playing during the lineup's first half's success)
Dave:
The Mavericks are supposedly one of the NBA teams that use this kind of data to set their lineups and exploit certain five on five matchups (the decision to start Barea during the 2011 playoffs was reportedly a result of Dallas using these kinds of stats).
I think the five man plus/minus lineup data can be useful provided that the sample size is large enough and provided that the coach using the data can figure out why a certain lineup is effective and how to maximize that effectiveness; for instance, the Mavs' opponents could not deal with Barea's dribble penetration, a skill set that Jason Kidd no longer has (Kidd has transformed himself into a spotup shooter). Perhaps the plus/minus data provided "proof" of this but I think that an observant coach or scout could notice this without using stats; last year's Lakers had no defender other than Kobe Bryant who could stay in front of quick pgs and Bryant lost his ability to do that after severely spraining his ankle in the first round (though Phil Jackson still put him on Chris Paul in certain situations just because the Lakers had no other viable options). J.J. Barea's quickness clearly presented a problem for the Lakers, with or without plus/minus data.
One of the problems with determining how effective it is to base lineups on plus/minus data is that teams that are doing this are understandably reluctant to publicly explain their methodologies (how they calculate the data, how they use it and so forth).
Using plus/minus as a tool to create the most advantageous five man lineup makes a lot more sense than asserting that individual plus/minus data can be used to definitively rank the league's players.
Post a Comment
<< Home