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February 8, 2006

An Interview with MGL
by SG

Mitchel Lichtman, better known in the on-line baseball community as MGL, is one of the foremost experts in the field of sabermetrics today. He is best known as the inventor of UZR (Ultimate Zone Rating), the most advanced form of defensive statistical analysis currently available. Although he now consults for a major league baseball team and UZR has become proprietary, he is still willing to share some of the results every year as well as his other methods of player evaluation. MGL has collaborated with Tom Tango and Andy Dolphin to write a new book about baseball strategy called The Book, about which more information can be found here. MGL agreed to do a collaborative interview with Replacement Level Yankee Weblog and to discuss the upcoming book as well as some general Yankee questions.

1) Assuming no more roster moves of any significance, how do you see the AL East playing out?

MGL: Despite some major roster moves and some serious spending by Toronto, unfortunately for them and for their fans, I expect the final standings to be similar to last year and to recent years.

With Boston and the Yankees spending money as they can afford to do and still having a core group of excellent players, they will be the powerhouses of the division again, barring the usual, such as major injuries, major bad luck for them, or good luck for one of the other teams.

Toronto will have excellent pitching on the strength of the best one, two combination in baseball, and one of the best closers in baseball, assuming they all remain reasonably healthy. Their offense, however, and infield defense, leave a lot to be desired, for a contending team at least. They got rid of their only offensive superstar in Delgado, and while Glaus can hit a bunch, he appears to be a defensive liability. Adams is a terrible defender and moving Hill from third to second will not help either. Overall, I project them at 87 wins and third place, which is not bad actually. Maybe it is considering how much money they spent – I don’t know. If any of their pitchers breaks down, especially Halladay or Burnett, or even Ryan, they could easily struggle to post 80 wins.

Tampa, despite some people’s optimism, is still not a good team. We should, however, see major improvement in their w/l record, although much of that will come from the “plexiglass” principle (essentially regression toward the mean) alone. Their offense and defense will be sub-par again, though not as bad as last year. Their pitching will be pretty bad again. The only remotely decent pitcher on the staff is Kazmir, who is and was the real deal, for all you Met fans (while Zambrano never was). Baez was a below-average closer and rest of the pen is still pretty weak. Look for them to win 76 games at best.

Baltimore could be the surprise team of the division. After a hot start last year, they basically were unlucky for the season and should have won 80 games or so based on their underlying statistics, as well as their player projections going into the season. They have a core group of outstanding players (only one of whom is a household name) in Tejada, Roberts, and Mora, and Bedard and Cabrera are well-above average pitchers. Look for the O’s to win 86 games, good for fourth place.

As I said, Boston and the Yankees are by far the cream of the crop in the division. Boston has incredible depth in their starting pitching. How many teams would love to have Clement and Arroyo batting for the 5th slot in the rotation? Heck, on a few teams, either of those guys would be the ace of the staff. Of course if Beckett does not remain healthy and Schilling does not regain at least some of his pre-2005 form, their pitching will not be nearly as good as I expect it to be. Also, having Timlin rather than a healthy Foulke as their closer, is not going to help their pen. I expect them to win around 94 games, assuming everyone stays reasonably healthy, good enough for second place in the division and an excellent shot at the Wild Card again.

The Yankees have a powerhouse of a lineup again this year. The only weakness is at DH, and even that is not too bad. With a little luck, they could score 1000 runs in 2006. I think that 900 is a slam dunk. Their starting pitching, one through four, is pretty good, if RJ stays healthy and keep his velocity consistently in the mid 90’s. Mussina, while well on the downslope of his great career, should still be able to post good numbers, and while Wang and Chacon are not as good as they pitched for the Yankees last year (especially Chacon), they are still pretty decent pitchers. And of course, Mo remains one of the best closers in baseball. Pavano and Wright are the stepchildren in the back of the rotation this year. I much prefer Pavano. I think Wright is a terrible pitcher who had a good, flukey year for Atlanta in 04, perhaps helped by the tutelage of Mazzone. I expect the Yankees to once again lead the division, this time with 96 or 97 wins.

Of course, the better you are, the more hurt you are by injuries and other unforeseen circumstances, so you never know. The plexiglass principle also applies when projecting player and team performance.

2) What do you see going forward for Robinson Cano and Chien-Ming Wang? Andy Phillips looks like he may be used in a fairly significant role in 2006. How do you think he can do based on his minor league performance? What do you think about the Yankees farm? Which home grown players do you see benefiting the team the most this next year? 2 years down the line? Is Phillip Hughes too far away for you to give an opinion on?

MGL: I know that they are popular discussion topics for fans, but the minor leagues and prospects are not my forte. That being said, I think that Cano is the real deal and should help the Yankees for years to come. His hitting was surprisingly good last year, and should regress a little, given his modest MLE’s in the minors. There are some differences of opinion as far as his defense goes. UZR has him as slightly below average in 05. I have heard others say that he is not that bad. If his defense ends up being above average, he is quite a valuable commodity. If it ends up being sub-par, then he won’t be so valuable.

As I said, I think that Wang is the real deal too, and ought to remain an above-average starter, which is a very valuable commodity, given that league-average FA starters command 8 mil a year or so. He was very good (his MLE) in the minors so it was not surprising that he would have pitched so well in 05.

Andy Phillips ought to be playing somewhere in the majors. He is a good hitter. I don’t know much about his defense and I don’t know whether his natural position is second or third. He is much more valuable if he can play second (adequately) of course. If he is slated to play second, the Yankees would need to trade either him or Cano, both of whom ought to be powerful trade bait I would think. If he is touted for third base, then they need to move A-Rod back to SS (where he belongs) and Jeter to somewhere else (where he belongs). I don’t see that happening any time soon.

Just scanning my MLE’s, the Yankees appear to have a fine crop of hitters at Columbus but not at Trenton.

3) On the major league side, there is obviously concern with the ages of several Yankee players. Are there any warning signs with Jason Giambi and Gary Sheffield that we should be wary of? How do you see Johnny Damon holding up over the next four years, and how much did the Yankees overpay for him?

MGL: Because of the steroid situation, Giambi will always be somewhat of a question mark. He works out at a gym a few minutes from where I live, and from what I understand he is still (sans PED’s) in great shape (and a heck of a nice guy they say).

Sheff’s defense is not good at all, but he can still hit the heck out of the ball. There really is no such thing as a “warning sign” as far as projecting a player to precipitously or suddenly decline in performance. Players over the age of 26 generally (and without chemical enhancements) start to decline overall offensively. Over the age of 30, they decline quite a bit each year, and over the age of 35, they decline even more each year.

BTW, players generally decline defensively starting from a very early age (early 20’s), much like the aging curve for their triples rate. First base defense might be an exception to that rule. Anyway, we should still see Sheff and Giambi hitting well-above average for their positions, although not nearly as well as they hit 3 or 4 years ago.

I don’t know how well Damon will or will not “hold up.” Fast players tend to age better than slow ones, which is a good sign for him, although almost all CF’er s are fast, right? His defense appears to be not nearly as good as it once was (and of course his arm is a rag, although the Yankees should be used to that in CF), which was one reason why Boston let him go I think. He can still hit well for a CF’er and runs the bases well. As with most long-term contracts, you pay for current expected performance and hope that a player’s decline with age (assuming he is past his prime), and chance of major injury, is balanced by salary inflation.

How much did the Yankees overpay for Damon? That’s a leading question! Given that he projects to be about 3 wins above replacement this year, that is worth about 8-10 mil on the open (FA) market for a CF’er, I suppose. Personally, I would not have paid him more than 7 or 8 mil a year (my personal limit per marginal win is around 2 mil). And as I said, although long-term contracts tend to get balanced by inflation, 4 years is a little long for a 32 year-old. By Yankee standards though, 13 mil a year is not that bad, maybe about 40-50% more than he is actually worth in the open market.

4) The Yankee defense has been a sore spot for quite a while. How do they project defensively in 2006? Can you share any 2005 UZRs for any of the Yankees? Is there any potential beneficial effect on the LF and RF due to the upgrade from Bernie Williams to Damon?

MGL: First, I don’t think that one player’s defense really impacts another.

As I said, although Bernie was terrible in CF, Damon may not be that good himself. I don’t expect the Yankee defense to be much better than last year, especially with Giambi now full-time at first (which makes up for the Bernie to Damon upgrade in center). But who cares about defense (other than the pitchers’ agents) when you have that kind of offense?

Pound for pound, a run saved on defense (or pitching) is a smidgen better than a run gained on offense, but for all practical purposes, they are one and the same. Defense and offense combined, the Yankees have by far the best starting lineup in baseball. Although they don’t have the best pitching, they are probably the best overall team in baseball as well.

Here are some 2005 UZR’s for the Yankees. Keep in mind that one year UZR’s don’t tell you a whole lot about a player’s true defensive value (or his defensive projection). For that, you want multi-year UZR’s. For example, Giambi has generally been quite minus in the past. A-Rod is usually much better than 2005 (historically he is a GG caliber SS), Damon has been better, and Sheff is usually not that bad. Posada is probably not as good as his 05 defensive numbers either.

Giambi 0
Cano -1
Jeter -8
A-Rod +1
Matsui -2
Bernie/Damon -12/-6
Sheff -20
Posada +4

5) The subject matter of your new book, The Book, looks very intriguing to me, particularly the sections about bunting and optimizing a lineup. Have you analyzed any managers' tendencies in this? If so, how would you rate Joe Torre in this regard? I also wonder if bullpen usage is something you tackle in The Book?

MGL: Yes, we have a nice chapter or two on bullpen usage. We mostly talk about the best times to bring in your best reliever (your closer), as well as the use of LOOGY’s, ROOGY’s, and “platooning” pitchers in general. We talk about other things regarding bullpen (and starter) usage as well. Keep in mind that we go into quite a bit of statistical detail throughout the book. It is not “light bedtime reading.”

From time to time we mention a particular manager or two, but we don’t discuss manager tendencies per se.

I used to think that Torre was one of the better strategic managers in baseball, but I have since changed my mind for various reasons (not the least of which was when he started Enrique Wilson twice in the ALCS versus Pedro because Wilson had “done well” against him in the past). He is probably not a whole better or worse than any other manager, which would give him a C- in my class. One thing I do like that he tends to do in the playoffs is use Rivera for two-inning saves. He doesn’t do that enough in the regular season though. No managers do.

6) Torre is obsessed with pitcher/batter matchups when making out lineups. Most of us think this is folly based on the small sample size. Is there any predictive value to a particular type of batter/pitcher matchup? If so, what kind of predictive value do past results give to future performances?

MGL: See my comments in the last section. Funny, I didn’t know you were going to ask that when I mentioned the Pedro/Wilson thing! I won’t answer your question about batter/pitcher matchups in general. I’ll let your readers find out by reading The Book. The analysis we do is fascinating, if I may say so myself.

By the way, if any readers are uncomfortable with me touting The Book, please keep in mind that 100% of my proceeds from book sales are being donated to Retrosheet. So if you are on the fence with regard to buying the book, if you want to support Retrosheet (, a wonderful volunteer organization that compiles data for research, get off the fence!

7) What makes you believe UZR is a better defensive metric than other's metrics like standard Zone Rating (and all the variations of it), David Gassko's range, David Pinto's PMR, and Baseball Prospectus's Davenport fielding numbers? Is there such a thing as one, 'best', defensive metric?

MGL: While all of those you mentioned are good (among others not mentioned), some are better than others, by virtue of the data used and the breadth and depth (essentially the rigor) of the methodology used to “crunch” that data. For example, BP’s DFT’s do not use PBP data, nor does Gassko’s “Range.” Or Bill James’ Defensive Win Shares. Although the “Range” methodology is excellent (DFT’s are a “black box” so I can’t comment on their methodology), the value of a non-PBP based defensive metric is limited. Pinto’s PMR (and a couple of other PBP-based metrics) suffer from some methodological problems (or weaknesses at least) in my opinion.

The current incarnation of UZR (which is different from the “published” version), is extremely sound and uses very granular data (from STATS Inc.). It is very good in the “adjustments” it makes (the handedness of the batter, the park, the speed of the batted ball, the base/outs state, etc.).

STATS Zone Rating is fine. It just doesn’t make very good use of the data. For example, a soft ground ball in one location is treated the same as a hard one, and a fly ball in the outfield is treated the same as a line drive (I think). As well, all balls in a fielder’s zone are treated the same regardless of their actual location (5 feet from the fielder or 15 feet). There are no park adjustments either. That makes a big difference in parks like Colorado, and in left field at Fenway, for example.

All of that makes ZR sound bad, but it really is quite good, especially when it is expressed as runs saved or earned so that a person can combine it with offensive RC or linear weights. All of those things that ZR does not account for (which UZR does) tend to even out in the long run, so the larger the sample, the more ZR will agree with UZR and other good PBP-based metrics. There is still much work to be done with defensive metrics, but most of the work is in recording more granular data (like the exact speed, trajectory and “hang time” of batted balls, and the location of the fielders before the play emerges) and making the best use of that data. I think that we are 90% of the way there though, at least as far as UZR and other good PBP metrics are concerned. Some people would disagree with me.

8) What flaws, if any, can you point out in your own metric as well as in the other aforementioned metrics?

MGL: I think I addressed some of that already. The accuracy of the data being recorded is always a problem. Also, not knowing the exact position of the fielders is a problem. Discretionary plays, like a fly ball that more than one fielder can easily catch is problematic as well.

Most of the metrics can make better use of subjective information, which is not usually included in the data. For example, knowing that a certain play was “easy and routine” in the opinion of the observer/data recorder, or “spectacular,” or “could not have been gotten by anyone,” is extremely useful information above and beyond the location of the batted ball, and even the location of the fielder as well. None of the metrics mentioned herein utilize such information as far as I am aware (although there are proprietary systems that do). I am currently working on adding some subjective data to UZR (STATS provides a “judgment” on all plays made).

The ideal system or “holy grail” of defense metrics really is a combination of objective “data crunching” (using very granular data of course) and subjective observation (on a play by play basis – I am not taking about traditional “scouting”). That is true for offense and even pitching, BTW.

9) For offensive statistics, which publicly available statistic do you think encompasses the best combination of value-adding features of batters? I know you prefer your version of linear weights(SLWTS) which incorporate baserunning and defense. Is there the publicly available data to construct a reasonable facsimile of those? Also, what is your preferred method of evaluating pitchers, and do you treat relievers and starters separately? If you had to use publicly available stats without calculation for evaluating hitters and pitchers, what would you choose?

MGL: Let me start by saying this. I don’t know what you mean by “value-adding features.” Whenever I talk about a metric for evaluating batters or pitchers (or for defense), I am talking about a player’s “true talent.” IOW, it answers the question, “Who would you rather have on your team (a generic team) in the future if you were interested in winning the most games you could (not counting playing time or chances of injury)?” As far as value in the past or in a certain context, as in evaluating past performance for an MVP-type award, I don’t know what the best statistics are, and that doesn’t interest me anyway. So keep that in mind as I answer these questions.

Let me start with the last one. Of course, these days when you say “publicly available,” that could mean on Baseball Prospectus or it could mean on ESPN or Fox Sports. If you mean “mainstream publicly available,” which I assume you do, then ERA and OPS are the best stats to use. Anything else (mainstream) adds nothing to the argument. Keep in mind a few things if you use raw OPS or ERA. One, one year does not a projection (or an estimate of “true talent”) make. IOW, sample size beware, and learn how to do some rudimentary “regression toward the mean.”

Two, always place raw numbers into context with league averages. For example, in 2001, the strike zone was changed and league average OPS and ERA went down. The players’ overall talent did not change.

Three, even without any numbers, mentally do some park adjusting if you can. A player who plays half in games in Colorado will not have nearly the same raw numbers as an equivalently talented player who plays half his games in Dodger Stadium. We all know that though, right?

Four, you really should compare players at the same defensive position or mentally make an adjustment for that position. For example, the average first baseman hits 20 runs per year or around 100 points better in OPS. So if you are comparing one player to another and they play different positions make sure you at least mentally make some kind of positional adjustment. As a rule of thumb, first basemen and corner OF’ers are 10 runs better per year at hitting than the league average batter, CF’ers and third baseman are average, second baseman are 5 runs worse, SS are 10 runs worse, and catchers are 15 runs worse.

When comparing pitchers, you must also compare apples to apples. That means that you should not use any metric to compare a reliever to a starter, “straight up.” For example, the same pitcher when relieving (one inning or so), is likely to post an ERA almost one run better than when starting, with some caveats. We talk about that in The Book, BTW. Also, when evaluating relievers, forget about “strand rates” and all that nonsense (again, assuming you are evaluating for projection purposes). Adjusted (for park and league) ERA is still the way to go for relievers as well as starters. Of course, I am still talking about “publicly available” stats. There are better ways to evaluate and project pitchers.

For example, the best way to evaluate pitchers is to use ERC which is “component ERA,” or translating a pitcher’s component stats (s,d,t,hr,bb+hp,so) into an ERA looking stat, using a linear weights formula or better yet, something called Base Runs (linear weights works best when a player does not impact himself; for teams and pitchers, where the player or team impacts itself, Base Runs works better).

That takes away the “luck” associated with ERA. There is no evidence that one pitcher is able to “control” his ERA better than another – only that one pitcher is better able to “control” his K, BB, HR, and to a lesser extent, his singles, doubles, and triples rates. That is why ERC works better for estimating true talent or projecting future performance than ERA. In the long run, ERA will approach ERC as the “luck” associated with ERA tends to even out.

Since regression to the mean is an integral and important part of estimating a player’s true talent and projecting his future performance (we also discuss that in The Book), one way to do that is to use a pitcher’s DIPS ERA or FIP rather than actual ERA or ERC. The less data you have, the more you should consider using DIPS or FIP to project and compare pitchers, since DIPS and FIP are essentially an extreme way of regressing portions of a pitcher’s component stats. If you want to know more about DIPS and FIP, do a search on the web. It is too complicated for me to explain herein. For batters and offensive metrics, you will have to do the “regressing to the mean” yourself (in order to take sample stats and “convert” them to a projection or an estimate of true talent).

For batters, and for offense, if you have access to more than OPS, you want to use a linear weights type formula. In my Superlwts, I simply add defense and baserunning (and a few other things) to an offensive linear weights formula. Also, my linear weights formula is a little more rigorous than the traditional ones (for example, it gives different weights to ground outs and fly outs depending on the handedness of the batter and includes RBOE’s).

If you only have access to OPS and say ZR for defense, it is tough to “add” the two together as they are not of the same scale. That is why I prefer all metrics to be in “runs” above or below average. That way you can add them all up to come up with a total value for a player. As a rule of thumb, keep in mind that good hitters (say an OPS of over .800) are usually around 10 to 20 runs above average per season, great hitters are 20-30 runs above average (OPS of .850 to .900) and superstars (OPS of over .900) are 30 to 60 runs above average in offense. (Bonds in his heyday is in a class by himself.) The superstar class is the likes of Pujols and A-Rod. On defense, the best players are 20 runs above average (and the worst are 20 runs below average) per season. And good ones are 10 runs better or worse than average. So for example, Rolen is around 30 runs in offense better than average and another 15 to 20 on defense. Jeter is 10 to 15 runs above average in offense and -10 runs in defense.

As you can see, the spread in talent in offense is about twice that of defense. BTW, baserunning adds or subtracts another 3 or 4 runs a year to a player’s overall talent for the best and worst baserunners. Outfield arms (and turning the GDP for IF’ers) are worth another 4 or 5 runs at best (or worst).

10) The Yankees are talking about batting Johnny Damon leadoff even though he projects to have the 7th lowest OBP on the Yankees by ZiPS. Is there such a thing as an optimal lineup construction, a formula or procedure for ordering players, that is universally applicable to all teams in MLB? Does staggering lefties and righties in the lineup help nullify platoon advantages, and is that something that is analyzed in The Book?

MGL: Yes, we have a great chapter on optimizing lineups. Since the exact order of the lineup rarely matters that much, you always want to avoid having two lefties batting next to each other, if at all possible.

As far as optimizing a lineup based on the exact composition of the players, yes there is an exact “formula” or algorithm you can use to do that. It balances leveraging each player’s strengths and weaknesses (power, OBP, etc.) with the fact that each lineup slot gets about .1 more PA per game than the one below it. If a manager (or fan) does not want to use the exact “formulas” we also give some “rules of thumb” for optimizing a lineup.

11) In a strict sabermetric sense, if you're the manager, and Barry Bonds comes up bat, do you ever walk him? What situational characteristics must be present for your decision to be more or less absolute?

MGL: Again, we have an excellent chapter on when and when not to issue the IBB. With Bonds there are times to issue the walk and times to not. In general, he is walked too much, at least over the last few years. Most managers are about using risk-averse (or “getting fired or lambasted in the media-averse”) strategies rather than the “correct” (the ones that give your team the best chance of winning the game without sacrificing future wins) ones. Of course, who knows the correct ones in the first place?

Like most anything else, all you can do is ask the experts. You can’t expect a manager to know what the optimal strategies and decisions are off the top of his head. That is impossible unless he is some kind of a savant. In order to figure them out, it usually takes some heavy statistical analysis and research. The problem of course, is that managers generally think they know the correct strategies, which is ludicrous of course, and scoff when someone suggests that they can find out if they really want to (like by reading our book).

It is a good thing for the consumer that most corporations are not run like baseball teams are run. Can you imagine the corporate CEO or manager of SONY trying to figure out the best way to manufacture a computer or television by intuition?

12) After all your years of research, what do you believe regarding the notion of 'clutch?' And in either case, what situations do you use to come up with that decision?

MGL: Another great chapter in The Book (are you sure you haven’t stolen a copy of the manuscript?). Andy Dolphin has done the best study on the existence of and predictive value of clutch hitting I’ve ever seen. His results are different than what most prior researchers arrived at.

13) Based on in-game managerial decisions, do you feel there are any managers in major league (or minor league) baseball that constitute a greater value added in terms of runs scored/allowed? Maybe a top 5, or bottom 5 list? Where would Torre rank? Is there even a way to quantify all managerial decisions based on runs added over average, etc?

MGL: Sure, you could quantify the value of managerial decisions, like the IBB, sac bunt, stolen base, use of the bullpen, etc. I’ve never done it and have never seen it done. It would take a lot of work and you would have to know the value of the various alternatives in the first place.

Most of that would show up in the runs scored and runs allowed so this notion that you can somehow evaluate a manager by the difference between his team’s actual and Pythagorean w/l percentage is nonsense. A few things like properly leveraging your relievers (like bringing in your best relievers when it counts the most and your worst relievers when it counts the least, regardless of the inning and score, although inning and score are related to leverage of course) will not show up (as much) in a team’s runs scored/allowed, but will impact their w/l record. But there is still too much noise in both a team’s actual and Pythagorean record to make any sense of it in terms of evaluating a manager. Maybe after 10 or 20 years you might find something.

As far as Torre is concerned, as I said, I used to think he was better than most, but now I am of the opinion (loosely based on fact and evidence) that he is middle of the pack, maybe a tad better than the average manager. I think part of the illusion that he is a good tactician comes from the fact that he has had such a good team over the last 10 years that he has had fewer opportunities than most managers to do stupid things.

In any case, I don’t think that the actual spread of manager talent amounts to more than a few runs a year. Of course I am talking about tactical things, not about teaching and motivating players, which I am sure are a big part (maybe even the most important part) of a manager’s skill set. On the other hand, if I were able to instruct a manager in the fine points of all of these things we are talking about and more, and they would listen, or they would simply read a book like ours, I firmly believe I could add 2-3 wins to a team’s w/l record at the drop of a hat. And you know what 2-3 wins is worth in today’s player market!

14) Of all the good-old 'traditional' baseball practices out there, like batting a speedy contact hitter first, etc., is there any one practice that truly makes you cringe when you see it happen?

MGL: There are lots. Without giving away too many of the book’s secrets, batting a poor but speedy (and good bunter or contact hitter) batter in the “two hole” is one. Sacrifice bunting a pitcher with first and third and one out is another. Sacrifice bunting a good-hitting (or even average-hitting) pitcher with one out and a runner on first only is a terrible mistake as well. There are lots more.

15) You have been working in an advisory capacity for a major league team for some time. What surprised you most about the inner workings of a major league front office? To what extent do you feel statistics are used by major league teams now? Besides offense and pitching, are they using defensive metrics? Are there inroads being made into new, under-appreciated skills in the current marketplace as the price of OBP has gone up?

MGL: Many, if not most teams, are using statistical analysis to some degree or another. Only a few are using advanced techniques and employ competent analysts and sabermetricians. Of course I don’t know for sure. This is conjecture on my part. More and more teams will of course do so in the future and some teams will be reluctant for a long time, for one reason or another.

There are some teams using advanced defensive metrics as far as I know. Not many though. The concept outlined in Moneyball and parroted ad nauseam in the media, that “OPB was the skill undervalued by teams,” and the thing that Beane and the A’s were able to take advantage of, is silly. As long as there are some teams that are better than others in doing anything, be it scouting, drafting, or analyzing player performance and strategies using advanced statistical techniques, there will always be players and situations that are undervalued and overvalued, and there will always be teams (the ones who are better than the other teams) that can take advantage of these things, and the market in general.

The fact that statistical evaluation of players and rigorous player projections are so valuable and so important simply means that if you can do those things well (which only a small minority of teams presently can) you will have lots of opportunities to take advantage of teams that don’t do those things well or at all. It has nothing to do with OBP or defense per se being over or under-valued in the market. That was an oversimplification and somewhat of a fiction made popular by a book and by an author who knew nothing about baseball or sabermetrics, as far as I know.

16) Can you tell us a little more about The Book, and your co-authors? How long has this project been in the works, and did any of the things you researched really surprise you?

MGL: I’ve talked a lot about the book already. I think it is groundbreaking. A little gory in the math department, but not so much that the average fan won’t appreciate it I don’t think. There are excerpts from every chapter on our web site ( and a brief description of the book itself.

My co-authors are Tom Tango and Andy Dolphin. They both have their own web sites devoted to baseball and other sports. They are brilliant sabermetricians and Andy is a brilliant mathematician/statistician as well. We have been doing research and working on writing the book for almost three years now I think. Writing a book like this is not as easy as some might think, especially when you can’t just sit down and “write away” like I am doing now. Practically every word in the book is based on hours and hours of sometimes painful research and analysis.

17) When and where can fans like myself, and anyone else who has enjoyed what they have read here, get your book, and how much will it cost?

MGL: Again, the web site is All the info is there including a link to purchase the book. The pre-order price is $16.95 plus $4.95 in S&H. The regular price once we start delivering is $18.95. We have free shipping on orders of 5 or more. I think the price is pretty reasonable.

The book has been a labor of love for us, and, as I said, 100% of my share of the proceeds is being donated to Retrosheet. Thanks for the opportunity to waggle my fingers while talking baseball, and good luck to the Yankees and all their fans.