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Tuesday, December 11, 2007

The Biz of Baseball: Zimbalist: Review: Diamond Dollars & The Baseball Economist

An Andrew Zimbalist production…as he reviews Vince Gennaro’s “Diamond Dollars: The Economics of Winning in Baseball” and J.C. Bradbury’s “The Baseball Economist.”

On Gennaro’s book…

Furthermore, Gennaro estimates his revenue data.  Here he makes some reasonable assumptions, but he also misses his target on some sources of revenue.  Despite these problems, Gennaro intrepidly forges ahead, glibly making specific claims about various teams’ win curves.  Unfortunately, most of the rest of Diamond Dollars suffers from similar weaknesses.

Detailed problems appear throughout the book.  Here is a small sample of these difficulties.  Gennaro does not adequately source his discussion.  The few footnotes and citations he does provide often confuse or obfuscate the matter.  He claims that he has developed a model to evaluate players’ productivity, but he neither explains the model nor does he cite the pioneering work of Gerald Scully in this field or its lineage.  Later in the book, Gennaro appears to assert authorship of the idea that baseball’s revenue sharing would be more effective if it were based on the value of a team’s market, rather than on a team’s revenue.  Yet this position has been amply discussed in the professional and journalistic literature.  Indeed, it is even incorporated into MLB’s latest collective bargaining agreement, which Gennaro entirely misses.

UPDATE!...J.C. Bradbury responds to to Zimbalist.

Repoz Posted: December 11, 2007 at 07:35 PM | 33 comment(s) Login to Bookmark
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   1. mr. man Posted: December 11, 2007 at 09:00 PM (#2641693)
Thanks for posting the review...I'm about to buy Gennaro's book (I still will, just because i want to see how he expands on Silver's marginal revenue curve), but I'm disappointed to hear that his work isn't sufficiently rigorous to pass the academic economist's test. I suppose that a guy with a business rather than economics background (Gennaro is an MBA and former PepsiCo exec) is more interested in explaining the ideas than in presenting exact scientific evidence. Like it or not, academics and hardcore baseball researchers will read it anyway, and leaving out the data will make the book more readable to a mainstream audience. Studes and Chris Antonetti are both quoted on Gennaro's website on the fact that it covers a lot of team management topics in a single volume in a way we haven't seen before. Most other baseball economics books have been a bit of a grab bag of unrelated topics.

I'm eager to know just how reliable Gennaro's estimates of individual team win curves are...can anyone help me on this? I'm in the process of writing my undergrad hon. econ thesis on whether teams consider their own marginal revenue functions in the free agent market, and whether teams on the playoff 'sweet spot' are paying more per marginal win. Nate Silver, are you out there?

I'm wondering at this point whether to test against Silver's model or Gennaro's update to it...
   2. birdlives is one crazy ninja Posted: December 11, 2007 at 09:28 PM (#2641725)
Gennaro also makes inaccurate claims about financial data. For example, he states that the NFL “generates over $2.5 billion in annual broadcast revenues” and that “about 80 percent of the NFL’s $5 billion in revenue is shared” (p. 4). The correct numbers would be over $3.5 billion, about 70 percent, and over $6 billion. On the next page, he writes that “$40 million from MLB’s central fund” is distributed equally to each team annually. The actual number in the last two years has been under $30 million. Such errors are not catastrophic, except when one tries to make detailed claims about a team’s revenue or a player’s value.

Only skimmed the review but if Zimbalist is going to offers counter figures, he should reveal his sources as well.
   3. Maury Brown Posted: December 11, 2007 at 09:37 PM (#2641737)
Only skimmed the review but if Zimbalist is going to offers counter figures, he should reveal his sources as well.
Zimbalist has been offered a platform to reply to JC's posting. I am also offering Vince space to offer up a rebuttal, as well.
   4. 185/456(GGC) Posted: December 11, 2007 at 09:39 PM (#2641742)
I skimmed the review myself, but I'll have to read it again after work. I was more interested in what Zimbalist had to say about Bradbury's work and that section seemed more interesting anyways.
   5. base ball chick Posted: December 11, 2007 at 09:51 PM (#2641755)
maury

can i ask you if you are also an economist? are you a lawyer like doug pappas was?

i don't mean that to be rude in any way. i am wondering what kind of viewpoint you are looking at things with

thanx
   6. Maury Brown Posted: December 11, 2007 at 10:06 PM (#2641769)
I am not an economist, nor a lawyer. I have been involved in sports business for years, including doing the Charter Seat License program for the submission to MLB regarding the MLB to Portland effort when the Expos were up for relocation. That has dovetailed into my continued growing career as a sports business analyst and reporter on that subject, and has allowed for some access. Honestly, my professional background involves the high-tech sector as a consultant for many large firms, notably the likes of Nike, etc.
   7. 185/456(GGC) Posted: December 12, 2007 at 12:17 AM (#2641849)
It's funny. the day that this is linked, I notice that Gennaro has an article at Yahoo! Sports.
   8. Mike Emeigh Posted: December 12, 2007 at 12:51 AM (#2641871)
It's funny. the day that this is linked, I notice that Gennaro has an article at Yahoo! Sports.


Link is now broken.

-- MWE
   9. 185/456(GGC) Posted: December 12, 2007 at 01:31 AM (#2641927)
I'm no good at linking Yahoo stories for whatever reason.


I am probably going to get kicked out of some club for this but I'm tempted to start my own This Week In Quotes feature:

Zimbalist’s critique is lacking and borderline dishonest in several places. - JC Bradbury

There also is the possiblity that Keith Law is not being honest in his post. Having been there and witnessed the events, I can assure you that there are several issues which Law alleges that are flat out lies, but if he didn't use the lies he wouldn't be able to make his point. - Tracy Ringolsby

I may be comparing apples oranges here, but Ringolsby's comment started a 417 post thread while there’s nary a peep about Bradbury calling a colleague a liar. Now, I’ll grant you that you actually have to RTFA to find Bradbury’s quote, but it smells like there’s a double standard here.
   10. GotowarMissAgnes Posted: December 12, 2007 at 01:51 AM (#2641952)
First of all, one of these things occurred during the weekend when traffic is much heavier.

Second, Bradbury replied under his own name and substantiated his claims with a detailed response to the review.

Ringolsby posted a one line firebomb under a handle, followed by several posts in which similarly wild accusations were made.
   11. Walt Davis Posted: December 12, 2007 at 01:52 AM (#2641954)
So far I've only read the first bit of Bradbury's response (and not Zimablist's review nor Bradbury's book ... so yes, back-asswards). Anyway this was raised:

He arrives at this outcome by running a multiple regression of runs on batting average, OBP and SLG. The coefficient on OBP is almost three times that on SLG.

This is one very odd regression and rather difficult to interpret.

The multicollinearity is an issue not so much because of its effect on standard errors (I agree with the thrust of Bradbury's response there though, depending on the size of those se's Zimbalist may have a point as well) but because of its effect on how the results need to be interpreted.

That "three times" larger coefficient is the impact of OBP, holding BA and SLG constant. That is, essentially, what is the impact of one extra point worth of walks. The SLG coeff is the impact of an increase in SLG, holding BA and OBP constant -- i.e. one extra point's worth of an extra base (e.g. a single becoming a double).

The BA coefficient has the oddest interpretation. Think about what it means to increase BA while holding OBP and SLG constant. To increase BA while holding OBP constant, you are essentially trading a walk for a single; to increase BA while holding SLG constant, you are essentially trading 1 double for 2 singles.

Whatever these coefficients might tell you, they don't tell you the relative impact of BA/OBP/SLG on scoring. And given what the coefficients are telling you, I'm not that surprised that OBP is three times as important -- it's the only coefficient where you're clearly trading an out for a non-out.

The "problem" is that BA (or hit-rate) is the primary component in both OBP and SLG. The estimated equation:

R = b0 + b1*BA + b2*OBP + b3*SLG + u

can be rewritten as:

R = b0 + b1*BA + b2*(BA+isoOBP) + b3*(BA+ISO) + u
R = b0 + (b1+b2+b3)*BA + b2*isoOBP + b3*ISO + u

(where isoOBP is a nonsensical term equalling OBP-BA)

and this clearly shows that one point of BA is way, way, way more important than the other two (unless one of those coeff's is largely negative).

(Alternatively you could think of it as a system of equations with OBP and SLG also endogenous (and a function of BA) and BA the only exogenous. In that case "b1" is the direct effect only of BA but the question is whether you want that direct effect or the total effect. I'd vote for the total effect. But that seems unnecessarily complicated.)

A cleaner formulation would surely be:

R = c0 + c1*(h/PA) + c2*((bb+hbp)/PA) + c3*(xb/PA) + e

Those variables will still be correlated (though much less so) but their interpretation is much cleaner. Increasing h/PA while keeping bb/PA and xb/PA constant is quite easy to comprehend (it's a single), even if it doesn't exactly give you the impact of BA. I assume the coefficients for the first two will be much larger since you are trading an out for a time on-base whereas the third is not. [Note, you assume the number of PAs stays constant since otherwise all 3 rates change.]

(Note, there are other issues -- you might want to standardise per 27 PA or possibly 27 outs; you'd want to control for baserunning; etc.)

And on the discussion about DIPS, ERA, etc. I've always felt that the "randomness" of ERA isn't so much due to variations in BABIP (though this obviously has an impact) but due to the "random" ordering of events. That is, whether you give up the walk before or after the HR or the double before/after the first out has huge impact on ERA even if they produce the same rate stats. Maybe that evens out more over a season than I think it does.
   12. Der Komminsk-sar Posted: December 12, 2007 at 02:01 AM (#2641960)
Now, I’ll grant you that you actually have to RTFA to find Bradbury’s quote, but it smells like there’s a double standard here.
I saw it - my eyes widened. I'd want to read Bradbury's book first before commenting here, though - my econometric chops are too rusty to go barging in just yet.
   13. Moloka'i Three-Finger Brown (Declino DeShields) Posted: December 12, 2007 at 02:02 AM (#2641962)
NERD FIGHT!!!!
   14. Greg Maddux School of Reflexive Profanity Posted: December 12, 2007 at 02:22 AM (#2641980)
it smells like there’s a double standard here.

Yes, there's one standard for subjects people give a #### about -- witness the large number of posts in BBWAA threads not involving Hat Guy, Jr. -- and another standard for subjects no one could give a tinker's damn about -- witness the dearth of activity in the Larry Fritsch Remembered thread.

But feel free to pretend you've uncovered damning evidence of some agenda.
   15. mr. man Posted: December 12, 2007 at 02:47 AM (#2642000)
Double standard? not really...both books are probably being held to too high a standard. Zimbalist is reviewing from the point of view of a journal referee, while both books are written for a general audience and the data is perhaps oversimplified for their benefit. Generally the academic standpoint is that you've got to have overwhelming evidence and rock solid methods to establish that a given phenomenon does or doesn't exist...

As for the OBP vs SLG comparison, I've got to side with bradbury...He makes it pretty clear that the effect is 3x more valuable for a -point- of OBP, not for a standard deviation's worth. I suppose one SD's worth would make a more useful comparison, but could be too compplicated to explain.

That said, I've read bradbury's book and found it was in most chapters just proving things most of us here already accepted to be true...or oversimplifying a more complex issue. I wouldn't have a problem recommending it to a new fan, but anyone who's been here awhile will feel like they've already read it.
   16. Phil Birnbaum Posted: December 12, 2007 at 03:21 AM (#2642040)
I've posted some comments on my blog.
   17. Maury Brown Posted: December 12, 2007 at 04:14 AM (#2642121)
Remember... The review is a republish from the Journal of Economic Literature. So, the original intent of the review was for an audience comprised completely of academics.
   18. mr. man Posted: December 12, 2007 at 04:27 AM (#2642137)
Thanks for the link, Phil. I hadn't realized how little attention or credence Zimbalist gives to recent Sabermetric work. It seems irresponsible to write anything academic on baseball economics without at least a solid understanding of the more well-known SABR stuff (James, DIPS, a fair bit of BPro). Does Zimbalist post on/read BTF?

I've been astonished in my readings of baseball economics how naive the academic community is about modern statistics. Even current journal articles still use AVG, RBI, wins etc for modelling purposes, totally oblivious to the fact that more modern metrics are available. I recall there being a bit of an uproar here over the fact that Hakes & Sauer used OBP and SLG to test the 'Moneyball Hypothesis' instead of the far more specific ISO and BB/PA.
   19. GuyM Posted: December 12, 2007 at 04:37 AM (#2642143)
As for the OBP vs SLG comparison, I've got to side with bradbury...He makes it pretty clear that the effect is 3x more valuable for a -point- of OBP, not for a standard deviation's worth.

Although I haven't read Bradbury's book, I do think Zimbalist's review read like he just went looking for things to slam. And not infrequently it appears that Bradbury has the better of the argument. That said, on this particular issue Bradbury is mistaken. Tango and others have shown quite definitively that a one point improvement in OBP is equal to a 1.8 point improvement in SLG. The three-to-one ratio is incorrect.

Interestingly , though, this makes surprisingly little difference when you actually evaluate players. Straight OPS, SLG+1.8*OBP, and SLG+3*OBP are all very highly correlated, because OBP and SLG are highly correlated. And that's one reason the whole Moneyball thesis is nonsense: there aren't enough hi-OBP/lo-SLG players to build a team around, even if OBP was "undervalued." (And of course the A's weren't a distinctly high-OBP team anyway.) You might save a few bucks by avoiding the occasional high-SLG/lo-OBP player, but were talking marginal gains not a fundamental team-building strategy.
   20. philly Posted: December 12, 2007 at 04:43 AM (#2642149)
Generally the academic standpoint is that you've got to have overwhelming evidence and rock solid methods to establish that a given phenomenon does or doesn't exist...


Well that certainly fits in well with a "publish or perish" culture, doesn't it?
   21. mr. man Posted: December 12, 2007 at 04:56 AM (#2642160)
Well that certainly fits in well with a "publish or perish" culture, doesn't it?


I'd say 'publish or perish' necessitates the aggressive criticism characteristic of journal referees, which is the root of zimbalist's need to go looking for faults. That much of what he criticizes in Bradbury's work is defensible isn't his problem; Zim's obligation is to raise all questions that could possibly be asked.

Not that he wasn't a little harsh about doing it!
   22. birdlives is one crazy ninja Posted: December 12, 2007 at 06:10 AM (#2642215)
Zimbalist is reviewing from the point of view of a journal referee,

Yeah, I guess he sort of is even though he's not actually serving as a reviewer for a peer review journal. He's writing for the bizofbaseball website thus it would have been nice to see a brief overview baseball economics, some contextualization of these books within that overview, a bit more of summary of the books, and then an explanation of the significance of these books, if any, within the field. Instead, the review is pretty much what a journal editor would get, a cut to the chase analysis of why the reviewer believes a particular piece of scholarly work is unpublishable in its current form.
   23. Phil Birnbaum Posted: December 12, 2007 at 06:21 AM (#2642221)
I answered Guy/19 at my blog, but will repeat here ... I agree that 1.8 is a much better estimate for the OBP/SLG ratio than 3. But I think Zimbalist came to the 1.8 conclusion for the wrong reasons -- his reasoning appearing to be that because SLG is larger than OBP, the coefficient is the wrong way to do things.

Of course, I may be wrong. Zimbalist writes, "If elasticity is used instead of the estimated coefficient, OBP is 1.8 times greater than SLG." I don't know what "elasticity" means in this context, but maybe he's actually fixing the flaw in Bradbury's work. Can someone clarify?
   24. Phil Birnbaum Posted: December 12, 2007 at 06:31 AM (#2642230)
Zimbalist writes, "[Bradbury] arrives at this outcome by running a multiple regression of runs on batting average, OBP and SLG. The coefficient on OBP is almost three times that on SLG."

If that's actually what Bradbury did (I can't find it in the book), it's quite possible. You'd expect 1.8 if you regressed on *only* OBP and SLG. By also including batting average, I bet you could easily wind up with the ratio of coefficients being 3.

For instance, suppose isolated power didn't matter at all. SLG would still be important, but exactly as important as BA. If you included BA in the regression, the coefficient of SLG would be zero, and the ratio wouldn't be 3, it would be *infinity*. But if you included only SLG and OBP, SLG would substitute for BA and you'd get the "real" answer.

If that makes sense.

(Note: this may be a variation of what Walt Davis said in comment 11.)
   25. mr. man Posted: December 12, 2007 at 06:33 AM (#2642231)
I'm guessing what zim is referring, to, phil, is that a 1% change in OBP is 1.8x the value of a 1% change in SLG.

That is, raising your OBP from .300 to .303 is 1.8x as valuable as raising your SLG from .400 to .404.

OTOH, he may be referring to the standard deviations...a standard deviation of SLG is much larger than a standard deviation of OBP and thus the two are of more comparable value in that regard.
   26. mr. man Posted: December 12, 2007 at 06:38 AM (#2642234)
The whole idea of using BA, SLG and OBP in a regression is kinda preposterous anyway because of the multicollinearity issues...beside the fact that a player's BA represents a significant portion of the variance in OBP and SLG, it's been shown several times over that players known to be slugging 'threats' will get an OBP bonus as pitchers will work around them and throw more balls. This effect may also depress their BA as the pitches outside the strike zone will turn some singles into strikeouts.
   27. Phil Birnbaum Posted: December 12, 2007 at 06:51 AM (#2642238)
25/mr. man: Thanks. If either of those are indeed what Zimbalist means, then I stand by my original point.
   28. mr. man Posted: December 12, 2007 at 06:56 AM (#2642242)
Right. It seems to me that Zimbalist (and maybe Bradbury needs to be careful whether they're talking about elasticity of SLG/OBP or elasticity of ISO/isolated walking?. The semantics are very important here. It may be the case that Bradbury was giving an accurate number, but an incorrect interpretation.
   29. Maury Brown Posted: December 12, 2007 at 08:07 AM (#2642287)
Not to derail the sabermetrics commentary... On Gennaro's book... Let me say in advance that Vince is a heck of a good guy. Like him a lot. However, in the multiple emails I've had with him over the months the one thing I have come back to over and over is the lack of showing how his figures are derived. There have been some figures presented in articles that have been far, far too squeaky clean. Example: A-Rod's dollars make sense for Yankees:
Combining Rodriguez's value over the life of the contract and considering the economic effect of the new Yankee Stadium set to open in 2009, he is likely to generate approximately $450-million of "value" for the Yankees, according to my analysis of his impact. Assuming the Yankees exceed the luxury-tax threshold in each of the 10 years and trigger the 40 percent luxury tax, the total cost for Rodriguez will come to $427 million.

[...]

Beyond Rodriguez's impact on franchise value is his impact on the value of the YES Network. Boras is doing his typical Pinocchio act when estimating it at $500 million or more, but it is reasonable to say the YES Network will be a more valuable asset – $50 to $100 million more over 10 years – because Rodriguez is a Yankee.
These figures are far too pretty, or in some senses, simply so broad as to allow one to wonder how much assumption is in the mix. The "$50 to $100 million more over 10 years" shows a whole lot of wiggle room. The "approx $450 million" is also just too clean.

In other words, I have to back Zimbalist on this:
For instance, Gennaro apparently has done some regression analysis where revenue is the dependent variable and team wins in the current and previous years are two of the arguments. We are not informed what the other independent variables are, nor are we told whether the relationship is tested linearly, nor for what years it is tested. Curiously, Gennaro does state that he has weighted the current and lagged team wins equally and that he has run a regression separately for each team to capture its distinct win curve. It is not clear how many years of data he has in each team regression or why he did not instead use team dummies and interactive variables in a pooled regression to identify these effects.

Furthermore, Gennaro estimates his revenue data. Here he makes some reasonable assumptions, but he also misses his target on some sources of revenue. Despite these problems, Gennaro intrepidly forges ahead, glibly making specific claims about various teams’ win curves. Unfortunately, most of the rest of Diamond Dollars suffers from similar weaknesses.
   30. Walt Davis Posted: December 12, 2007 at 08:39 AM (#2642298)
OTOH, he may be referring to the standard deviations...a standard deviation of SLG is much larger than a standard deviation of OBP and thus the two are of more comparable value in that regard.

At one point I looked at team runs for a few seasons (like 6 or so, nothing special) and looked at standardized coefficients (i.e. looking at the impact of standard deviation changes, not unit changes) and OBP and SLG came out essentially equal. I broke it up and did it season by season and that was kinda odd -- in about 1/3 of the seasons, SLG was much more important; in 1/3 OBP was much more important and in the others they were about equal. But it was a very small sample of seasons.

The whole idea of using BA, SLG and OBP in a regression is kinda preposterous anyway because of the multicollinearity issues.

Kinda. Multicollinearity is rarely a problem -- only when it's pretty extreme such as in cases where about 90% of the variance in one indep var can be explained by others. And that's not the case here. Even so, assuming the assumptions of linear regression are met, the coefficient estimates are unbaised and the standard error estimates are correct.

The bigger problem is the interpretation. Most of the explained variation in runs is being explained by the "collective" contribution of BA/OBP/SLG -- which is to say BA.

(Note: this may be a variation of what Walt Davis said in comment 11.)

In the same ballpark. The point I'm making is that the interpretation of any regression coefficient is "this is the impact of a 1-unit change in X1 holding all other X's constant." In the presence of multicollinearity, and especially in this specific case, the idea of changing X1 (BA) while holding the others (OBP and SLG) constant means that your coefficient is measuring the impact of a particularly odd sort of change.

That is, let's say your team hits 270/330/440. You might wonder "what happens if we add 5 points of BA?" Well, adding 5 points of BA would have your team hitting roughly 275/335/445 -- all three have changed. Therefore, the coefficient from this regression doesn't answer your question. This coefficient tells you how many more/less runs you'd score if your team hit 275/330/440. Basically if your team, say, traded 15 walks and 15 doubles for 30 singles.

Now that difference is close to zero, leading to the impression that BA doesn't matter. And at one level that's fine -- after controlling for OBP and SLG, BA matters little in terms of predicting team runs. But of course BA is the primary component of OBP and SLG.

Here's an analogous, more extreme situation. Let's say you ran a regression of team runs on OBP, SLG, other indicators of offensive quality, and the total salary paid to hitters. Now after controlling for the quality of the offense, why would paying extra money help? It probably doesn't. Does that mean money can't buy runs? Of course not -- money is how you buy OBP, SLG, etc. It does tell you that increasing offensive payroll without improving your offense is not likely to help but you already knew that. :-) (yes, obviously you could be buying better defenders)

And god forbid I should raise the spectre of the challenge of working with ratios again, but the fact that OBP is per PA and SLG is per AB means they should never be in the same regression. Yes, it probably doesn't matter a lot (and I did it myself in the regressions mentioned above). I support a constitutional amendment to measure them all per PA.
   31. GuyM Posted: December 12, 2007 at 10:59 AM (#2642318)
Good analysis by Walt. The way I think about it, assuming a regression on just OBP and SLG, is that you're really comparing the impact of OBP to the impact of ISO (isolated power), because that's basically what SLG becomes when you strip out the on-base benefit. When you realize you're really comparing OBP to ISO, not SLG, it's not surprising that OBP has more weight.

And using linear weights, it's easy to see that the proper weight for OBP vs. SLG is about 1.8. Adding one walk is worth about .5 runs (.33 for the walk, .17 for not making an out). Adding one base is worth about .3 runs. Account for the fact that OBP is based on PAs while SLG is based on ABs (increasing the value of the walk by about another 10%), and you get .55/.3 = 1.8.
   32. Phil Birnbaum Posted: December 12, 2007 at 02:42 PM (#2642396)
Walt/30: agreed. I think we're indeed saying the same thing in different ways.
   33. Maury Brown Posted: December 12, 2007 at 05:26 PM (#2642543)
This is one of those "drop-off-at-the-front-door-and-run" type of things...

Zimbalist has responded to J.C.'s blog posting. As I told Andy when I first read, prepare for the castle to be stormed by the sabermetric community. Here is an excerpt:
First, as I wrote in my review, I actually found the sabermetric part of Bradbury’s book to be interesting and useful. While I admit to not being a sabermetrics maven, I have read a significant amount of the literature and have certainly read Moneyball and a good deal of what Bill James has written over the years. Hoping that this does not sound too condescending, I think that sabermetrics contains many valuable insights, but I also think it has limitations. It is not now, and I don’t believe it ever will be, the dominant method applied in player scouting and evaluation.
The response could make for a nice thread on its own... will see what happens.

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