Last Thursday evening Henry Abbott of TrueHoop.com sent me an e-mail asking for my thoughts on a recent conversation Abbott had with Bill Simmons. What follows are these thoughts, which mostly center on what I think the primary task models are supposed to accomplish (hopefully this lengthy essay is more interesting than that last sentence).
Henry Abbott fights with Bill Simmons
This week ESPN.com listed the top centers of all-time. One of the newest ESPN.com employees – Henry Abbott (of the immensely useful TrueHoop.com) – was one of the people asked to vote. Abbott’s top ten excluded Moses Malone, which led to a protest from ESPN’s Bill Simmons. Simmons went so far to threaten to remove TrueHoop.com from his list of favorites, which would not only be wrong but just a bit extreme.
This was revealed at TrueHoop, along with Abbott’s justification for his choice. His justification centered not so much on the merits of Malone or other players, but the immense difficulty anyone has evaluating NBA players. The following paragraph captures Abbott’s basic argument:
In Phoenix they seem to believe excellent spacing and having everyone who isn’t Steve Nash limit their dribbling is the key. In New York it looks like Jamal Crawford’s ability to get Eddy Curry easy baskets is worth enough points a game to turn a loss into a win. I could go on and on. What it takes to win is subtle and elusive, like what makes a good meal. As much art as science. Which is not to say it’s random. It’s just inscrutable. Using one players’ individual’s points and rebounds as a major tool in that debate is like using a shovel as a major tool for brain surgery: so crude it hurts.
Thursday evening I received an e-mail from Abbott, asking me what I thought of his discussion with Simmons. What follows are some semi-random thoughts that hopefully lead to a simple, yet useful, observation:
Starting in Left Field: Predicting Presidential Elections
My discussion is going to start “out in left-field” on a subject far removed from basketball, and I think, immensely more complicated. Every four years the nation chooses a President. Millions of people participate in this event, and these people consider a seemingly endless supply of factors in making this decision. The list includes the positions the candidates take on a host of issues, the style and substance of their advertising, what the candidates look like, their political and family history, etc… Each voter attaches more or less weight to each element on this list of factors in making her/his final decision. Given the millions of people involved and the host of issues any voter could or could not consider, how can anyone possibly make sense of this event?
The answer to this question can be found in a book. Before there was The Wages of Wins there was Freakonomics. And before there was Freakonomics there was a little book called Predicting Presidential Elections and Other Things. This was written by Ray Fair (a Yale economics professor), and like The Wages of Wins and Freakonomics, Fair’s book takes research published in academic journals and puts it in a form accessible to non-academics.
Although Fair’s book covers such diverse topics as predicting the quality of wine, predicting race times in marathons as a person ages, and the likelihood someone would have an extramarital affair, I want to focus on his title subject, predicting presidential elections.
For the past thirty years Fair has been offering predictions of each election based on a fairly (sorry for the pun) simple model of voting. Fair’s model ignores most of what people think is “important” about presidential politics and instead focuses primarily on the state of the economy at the time the election occurs. In a nutshell, Fair finds that if the economy is doing well at the time of the election, the incumbent party tends to win. If the economy is doing poorly, the incumbent party tends to lose. In sum, Fair has been arguing for three decades that it really is “the economy, stupid.”
It’s important to note that Fair’s simple model explains about 90% of the vote. In other words, only about 10% of the vote is explained by the factors Fair ignores. And what does he ignore? Fair ignores such seemingly important issues like who the candidates actually are, what their positions on issues might be, whether or not they are popular, etc… In fact, right now, before the candidates are even chosen, Fair can offer a forecast of the 2008 election (one can look on Fair’s website for his January, 2007 forecast which might make Republicans a bit less happy).
Now does Fair’s model tell us that candidates are not important or that campaigns don’t matter? No, but it does tell us that if the economy is on your side (growing if you represent the incumbent party, not growing if you are the challenger) your campaign is much more likely to be successful. Likewise, without the economy on your side, your campaign is likely to have problems.
Building Models and the Scoring Focus
The purpose of this post is not to discuss presidential politics. I note the work of Fair because I think his work illustrates the task models are supposed to accomplish. A model is supposed to be a simplification of reality. And why do we need simple? Because when us human beings try and make sense of our world (so we can do stuff like make decisions) we tend to take what is very complex and simplify. If we did not do this, decisions would be extremely difficult to make. Given how we make decisions, a good model is most helpful when it allows us to simplify “correctly.”
What does all this tell us about basketball? Henry Abbott has noticed, as people probably have since James Naismith transformed “Duck on a Rock” into the game we love, that basketball is complicated. Wins seem to be about a multitude of factors including scoring, hitting the boards, passing, ball-handling, defense, creating shots, making teammates better, etc… Like voting in presidential elections, the list seems endless. Confronted with this seemingly endless list people wonder what we should focus upon. In other words, what on this list is truly important?
As we note in The Wages of Wins, decision-makers in basketball have simplified this list by focusing their attention primarily on scoring. We find that scoring is the primary factor behind what gets you paid and the awards the NBA gives out. Factors like shooting efficiency and turnovers are not given much consideration. The problem with this focus is not that decision-makers shouldn’t simplify, but rather that the focus on scoring – or how decision-makers simplified — leads to some predictable errors.
A Better Simplification
To see this point, let’s note that it’s possible to simplify basketball and arrive at a more accurate characterization of player performance. The big job in this analysis was done by the likes of Dean Oliver and John Hollinger, who (as Dean Oliver notes) in turn built on thinking of such people as Dean Smith and Frank McGuire. Basically, these people noted that wins in basketball are determined by how many points a team scores and surrenders per possession. In other words, offensive and defensive efficiency are what matters.
Of course, saying this doesn’t seem to help us evaluate individual players. Just like its not obvious how an individual player impacts wins, it also doesn’t seem clear how individuals impact a team’s efficiency measures. Fortunately, with a bit of statistical analysis, we can use the relationship between wins and efficiency to ascertain the value of the various statistics teams track for individual players.
And once we know the value of the player’s stats in terms of wins, we can then learn which factors are more important and which matter less.
The list of truly important factors is surprisingly small, and hopefully somewhat obvious. The primary factors that impact outcomes in basketball are shooting efficiency, rebounds, steals, and turnovers. In other words, a team must be able to convert its possessions into points. So shooting efficiency is important (or in other words, missing shots does not help a team win). Possessions – or rebounds, turnovers, and steals – are also important. You must take the ball away from your opponent before they score. And you must avoid giving the ball away before you score. So winning the turnover battle and hitting the boards also matters.
Now it’s not the case that factors like blocked shots, assists, and personal fouls don’t matter. But none of these factors are as important as shooting efficiency, turnovers and steals. And once we see this, we can understand the outcomes we observe.
For example, the Rockets lost Yao Ming to a devastating injury, yet managed to maintain their winning percentage. Once we see the importance of rebounding, though, we can see how having an extraordinary rebounder like Dikembe Mutombo come off the bench mitigated the loss of Yao.
We also see why the 76ers improved after Iverson departed. Iverson has problems hitting shots and avoiding turnovers, so despite his scoring totals, our model tells us he does not produce as many wins as his star power suggests. In other words, we should not have expected a team that replaced Iverson with Andre Miler to get worse (as many people who focused on scoring predicted).
The Simple Lesson Learned
The temptation in doing analysis – whether it is elections or basketball – is to consider everything that anyone thinks could matter. Models, though, are not supposed to consider everything. Models are supposed to be simplifications of reality that allow us to focus on the factor or factors that truly are important.
Let me put it another way: When an analyst ignores what a model is supposed to do, and tries to tell decision-makers the value of everything, the analyst ultimately tells the decision-maker nothing.
All this being said, one should not think the work of Fair is the final word in modeling presidential elections or the best possible model anyone will ever offer. Nor should people think Wins Produced, Win Score, PAWS, etc… are “perfect” models of player performance in the NBA.
I would argue, though, that these are all “good” models in the sense that each is both a simple and accurate reflection of reality, reflections that allow people to better understand the world they observe. And ultimately, this is what we want models and analysis to do. Simplify a complex world correctly, so people can make better decisions about the allocation of resources (which is all economics is really about).
Final Thought
Of course all this ignores the really important questions. Is Moses Malone one of the top ten centers of all time? And why did Bill Simmons – a life-time Boston fan – get that upset when Abbott left Malone off his list? After all, Malone never played for the Celtics. Perhaps this is something to discuss in the comments.
– DJ
Paulo
March 10, 2007
Hi dberri,
I’ve been a reader since November, but a first time commenter. I have since found your work to be really interesting, and a very good indication of production. I’ve been a long time reader of Bill Simmons. I didn’t really check into the voting results partly because I felt that the rankings were fair enough, given the expertise of the panel. It wasn’t until Simmons pointed out that Abbot left off Malone in the voting that I was aware of that. This also got me wondering, since he won consecutive MVP awards for two different teams, and I guess it was a decent, if not good, indication that he was producing numbers and wins despite different environments. Do teammates and systems matter in determining WP or PER? Yes. But up to a certain point, The talent of a player should shine no matter what the environment.
I really believe Simmons has a point. There are things that numbers can’t determine, and one has to watch a player to truly evaluate him. Charley Rosen, despite being one of the most (insert derogative term) writers, has a good eye for this. He may (not) have written about a ranking of all time centers, but I would assume that he would at least given a vote to Moses Malone. I would assume you would have given a vote to Moses Malone. Same with almost every basketball junkie in the entire world.
As for your final thoughts, Simmons gives due respect to Celtic antagonists. If you’re familiar with his body of work, he has highly praised Isiah Thomas (as a player), Magic, Jordan, Dr. J, Andrew Toney, Moncrief, Mo Cheeks (as a player), and likewise, Moses Malone. And yes, Malone deserves to be in the top ten, arguably even top five (it’s a coin toss between Hakeem and Malone for that one).
curious observer
March 10, 2007
Why do you link to TrueHoop but TrueHoop doesn’t link to you?
co again
March 10, 2007
How come Dan Rosenbaum never comments here, but silverbird does?
The Franchise
March 11, 2007
Why does one drive on a parkway and park on a driveway?
Kent
March 11, 2007
Why do cats eat spaghetti?
curious observer
March 11, 2007
If vegetarians eat vegetables, what do humanitarians eat?
Owen
March 11, 2007
Long post. Good post. Isn’t this a question that can be assessed statistically somewhat? Even if we dont have complete stats for Chamberlain, Russell, and Mikan, cant we ran some numbers. Compare Malone to Ewing or Walton, who seem the most replaceable to me. I suppose making that kind of career comparison is difficult using WP. Teams play at different paces. Different leagues. Who knows. It is difficult. I agree with Abbott that numbers cant completely sum up an entire basketball career.
I can’t agree with this:
“In New York it looks like Jamal Crawford’s ability to get Eddy Curry easy baskets is worth enough points a game to turn a loss into a win. I could go on and on. What it takes to win is subtle and elusive, like what makes a good meal. As much art as science. ”
What does that mean? Curry and Crawford? Give me a break.
Confucius
March 11, 2007
Basketball is pretty scrutable by numbers and by eye, maybe not absolutely but very far, as far as you wish to pursue and learn. it just takes time and many words and caveats. what is hard is to wire a basketball team to beat everyone else with high confidence or certainity given that
many of the things that a team is built on vibrating variables that are affected by environment and not fixed. Most people know that but try anyways. It is a game.
Confucius
March 11, 2007
82 games player pair data says Curry almost identical production with and without Crawford. Pretty close to same last season too but a little worse together.
nba.com current lenovo +/- stats show Curry only significant positive with David Lee. Essentially even with Nate Robinson and Steve Francis. Was a -3 per 48 minutes with Crawford according to 82 games as of 2/15.
If there is Curry /Crawford chemistry that others see by their eye, I can’t claim to have watched them but the stats make me ask how sure the eye is. Doesnt seem strong by stats.
Owen
March 11, 2007
yeah, totally ridiculous. He is saying that because of one play this year basically, when Crawford dished to Curry for a game winning alley oop. Thats how a reputation for great chemistry is built, although the stats tell a very different story.
Watching Jerry Stackhouse right now, this guy might need to be put in the Allan Houston, Allen Iverson group of overrated scorers.
Confucius
March 11, 2007
Crawford’s assists with Curry compared to not up but only by .3 to .4 this season, last season but FG% essentially the same and his own scoring down both seasons.
Some pairs show positive or negative synergies. this one doesnt seem to.
Confucius
March 11, 2007
Oh I see. Thanks Owen. I didnt know that specific instance.
The mind is impressionable.Must consider and reflect on the whole of experience and check and recheck from different angles and different light and understand yourself and your values and filtering and other mental habits to be wise.
Confucius
March 11, 2007
Mr Abbott was right that the most basic numbers alone are not enough and it is good to look beyond that. I don’t know offhand if Malone belongs in or out.
Henry is good at reaching out and considering varying opinions.
Rashad
March 12, 2007
I thought everyone would appreciate this onion article about VC.
http://www.theonion.com/content/node/59401?utm_source=onion_rss_daily
Mark T
March 12, 2007
I like Confucius’s post about Curry / Crawford / Lee. It points up the importance of rebounding. Lee does and Curry doesn’t. They complement each other well. And I agree with the authors that the accuracy of their statistical analysis can be tested, both backtested and via projections, and is in fact being proven when teams engage in real world experiments like Iverson trade.
I watched a DVD of some Celtics/Hawks games in the 80’s – these games are in the Larry Bird: A Basketball Legend set. What was remarkable to me was the Celtics’ success in rebounding, and avoiding turnovers, against an equally big and probably more athletic Atlanta Hawks team. It enabled them to win the games by maximizing possessions. Although they were individually slower than many teams today, they played each possession faster than most teams today, because their big men worked at both ends of the floor and at all facets of their game, including passing. They didn’t just stand around at the 3-point line.
Westy
March 12, 2007
Good post, Dave.
Owen
March 12, 2007
It’s been very interesting to see the reaction to David Lee being out in New York. Curry’s production has fallen sharply. According to this article, its because teams are doubling him more and more now that they arent afraid of Lee being loose on the boards. Probably the first time I have seen a rebounding specialist get credit for helping his high scoring teammate.
http://www.newsday.com/sports/basketball/knicks/ny-spkenb0311,0,7589804.column?coll=ny-sports-headlines
Confucius
March 12, 2007
Upon further reflection Moses Malone belonged.
I might have to take 10th place to overtime and consider McAdoo, Gilmore and Parish over Walton’s career (not just peak).
Owen
March 15, 2007
Paulo – No one responded to your original post. I should say that I too am both a die hard Bill Simmons fan, and an avid Wages of Wins reader. It’s become a very difficult split to pull out when it comes to NBA analysis. I find him extremely entertaining, but his posts on the NBA, replete with stories of “glue guys” and “chemistry” seem
kind of foolish after having immersed myself in this site.
The Iverson trade really brought out this conflict. My two main sources of NBA analysis had diametrically opposed views of the trade. I think the title of Simmons’ post was “Dont Question the Answer.”After forty games, it seems pretty clear that Simmons was completely wrong. You never know, jury is still out I suppose, but it looks that way. And it seems he has almost given himself a free pass for his mistake, although some of his other readers havent.
• To answer the two most common NBA questions from the past week — yes, there is some serious Ewing Theory potential with the Sixers right now, and no, I can’t even fathom how Isiah got an extension when his team is five games under .500 in a crappy conference with a $120 million payroll and no lottery pick in 2007.
Can you imagine the consequences for this website if Denver had gone 28-12? Really, the stacks were high in a way, and DB came out swinging and predicted exactly what has happened. Meanwhile, Bill Simmons whiffs on this biggest story of the NBA season, and catches no flack for it…
dberri
March 15, 2007
Owen,
Let me pretend to be an economist for a moment and comment on how incentives shape behavior. Bill Simmons does not write from the perspective of numbers. Sure he references these when they support what he is saying. But analyzing numbers is not his thing. And he has been very successful doing what he does. For him to argue at this point that one only needs to look at the numbers to get the answer would be against his self-interest. In my experience, and this is what economics teaches, people tend not to take positions that are against their own interest. So I do not expect Simmons to admit that he was wrong about Iverson.
The same can be said about the attacks on Wins Produced from the adjusted plus-minus crowd. These people are selling non box score methods of analysis to NBA teams. If it is the case that the box score stats can tell us who is “good” and “bad”, then why would NBA teams give the plus-minus folks money? Again, self-interest motivates this group as well.
Owen
March 15, 2007
I gotcha. I hadnt really understood that. Originally, I thought there was some sort of disconnect. Clearly though, there are a lot of people who will be impossible to convince since they have a vested interest in undermining your work. I think that would explain a lot of the animus I see out there, You really cant do much with that. As for the Sports Guy, he is very amusing, and he represents s lot of people out there who enjoy the game and dont care about box scores, which is fine.
Keep on posting, love your work.
dberri
March 15, 2007
Owen,
I don’t think I have done enough to explain that point to people. Rosenbaum and the people at 82games.com are interested in working for NBA teams. Hence the need to attack our work.
Frankly we did not anticipate any attack from people like this when we wrote the book. We fully expected people like Simmons to dislike the work. But the stats people we thought would be more open-minded. Unfortunately, when you are chasing dollars, an open mind is hard to maintain.
jake
March 18, 2007
My take: what’s been going on is that Rosenbaum and friends wanted to engage in a discussion with you, but they claim you’re not interested. Dan’s given examples on APBRmetrics of how you can change the weights you assign but still be able to predict wins just as accurately. It seems you have just as much incentive to not respond in order to protect your work, rep, etc.
dberri
March 19, 2007
Jake,
Let me get this straight. My co-authors and I write academic articles that are available to everyone. We have written a book with over 250 end notes explaining in detail what we do. We have a blog where I make entries virtually everyday and often respond to comments. After all this, you are saying that I am avoiding talking to people. That seems hard to believe.
A few words on Rosenbaum. He has attacked our work since before he ever read the book. One of his claims is that the weights we assign the various statistics is arbitrary. This is based on the fact that assists are not used to predict wins. If you read the book, this is quite clear. The forecast of wins appears on page 110. How assists are valued is detailed on page 117. As we note in the book, assists do not impact wins directly. What they do is impact the productivity of teammates. We determined how much of an impact assists have (via regression analysis) and this is used in our evaluation of players. If you altered the value of assists it would not change your forecasting power, because assists are not used to forecast (as the book clearly states). But changing the value of assists would change how much credit you are giving players for assists. And this change would contradict how we read the empirical evidence. This is not only detailed in the book, but also in the article “A Simple Measure of Worker Productivity in the National Basketball Association” (which should be published this summer).
I would add that Rosenbaum came to The Wages of Wins Journal and asked about assists. Well he came, but under an alias (which is a bit strange). Specifically he came twice, which led me to send a quick e-mail to his alias (which I took to be a high school student). This e-mail quoted from The Wages of Wins. Rosenbaum then took this e-mail, sent to his alias, and posted it at the APBRmetrics forum without my permission. Just to summarize. Rosenbaum lied about his identity in posting a comment. He then took my e-mail response to his alias and posted this without permission (misrepresenting what I said in the process). Does this sound like the behavior of a person looking to have “an honest discussion”?
This is not the only misbehavior on the part of Rosenbaum. As noted, he attacked our book before he ever read it. After supposedly reading it he continues with his attacks, which are often personal (calling me arrogant, questioning my honesty). In terms of the substance of his attacks, I have explained why using Wins Produced to predict adjusted plus-minus is inappropriate and how the team adjustment does not alter our conclusions. Despite these arguments, it makes no difference in Rosenbaum’s behavior. He just keeps repeating the same mistaken analysis no matter what we said in the book or what we say in this forum.
I would add that Rosenbaum has left out a few details regarding his qualifications. Although he is quick to note on-line that he is an economics professor (although only an assistant), he is slow to tell people that he has never published a paper on the subject of economics and sports. Given that it is your publications that people take as evidence of your expertise, a lack of publications indicates that you are not quite the expert you claim.
In the end, what I said earlier stands. Rosenbaum is in the business of selling a non box score method to NBA teams (a method he did not create, but copied from Wayne Winston). The Wages of Wins shows that box score stats do give you an accurate evaluation of players. Therefore his business is threatened by this book. I believe this has caused him to constantly attack me and The Wages of Wins. In the past year he has on multiple occasions said that we are arrogant (which may be true) and that we are dishonest (which is not true).
Again, I will repeat what I said at the onset of this comment (that has gone on too long). I do not see how we are hiding anything when everything we do is spelled out in various publications and on this forum.
AMEMSDORE
February 10, 2009
stimulating and educational, but would be suffering with something more on this topic?
RaiulBaztepo
March 28, 2009
Hello!
Very Interesting post! Thank you for such interesting resource!
PS: Sorry for my bad english, I’v just started to learn this language ;)
See you!
Your, Raiul Baztepo