UZR and Beyond! An Interview with Mitchel Lichtman

MLB: Seattle Mariners at Los Angeles Angels


Today we present Part III of our series on fielding metrics! We are joined by none other than Mitchel Lichtman, affectionately known as MGL, who will talk about his Ultimate Zone Rating and a whole lot more!!

Joe Hamrahi (JH): Generally speaking, but in as much detail as you can, please describe Ultimate Zone Rating.

Mitchel Lichtman (MGL): Thanks for asking. Being an analyst and not generally a promoter, I love these kinds of questions, rather than, “What do you think of the stats v. scouts debate?” or some such thing.

Actually, for a great description of UZR, read Dewan’s Fielding Bible. They use essentially the same methodology.

UZR uses a STATS Inc. database, rather than BIS, although I assume that the databases are very similar; at least they should be. I break the field down into “grids” or zones, much smaller than the zones that STATS uses for its zone ratings, based upon distance and location. The location is a “pie slice” from foul line to foul line, with 22 slices across the field, each one around 4 degrees wide of course.

John uses vectors and distance I believe, essentially an x. y coordinate on the field, for where an air ball lands or is caught or where a ground ball is caught or goes through the infield. Although STATS provides an x, y coordinate as well (from video also) in its data, I don’t like to use data that granular, as the sample sizes will be too small to generate a meaningful baseline probability of a ball being caught, unless you use a function to smooth out the data.

For example, let’s say that at point a, b, a line drive is caught 20% of the time, and at point c, d, a little further from a typical fielder location, it is caught 22% of the time, and at point e, f, a little further still, it is caught 11% of the time. Clearly you don’t want to use those exact numbers. You would want to use something like 22, 16, and 11, if you catch my drift. I don’t know whether John “smoothes” out those probabilities or not. That is the proper way to do it.

One reason that I absolutely cannot use the “coordinate methodology” (for lack of a better term) with no “smoothing” is that I have many more parameters than just distance and location. The sample sizes for each “bucket” would be miniscule if I did not use segments of the field that were a lot larger than one x, y coordinate. Of course, the proper way is to use a “smoothing function” and x, y coordinates, but alas I do not. Other analysts working for the Cardinals are presently working on this better methodology. That segues nicely into the next question.

Oh, before we get into that, I do essentially the same thing with the data and the baseline probabilities as John does. If a ball is turned into an out, that fielder gets credit for that portion of a “ball” that he normally does not convert into an out. For example, if he normally converts that ball (with all the concurrent parameters) into an out 60% of the time, he gets credit for .4 outs. Converting “balls” into runs is simple (and I don’t know why John did not do that before he wrote his book). An out is worth the value of an out (around .28 runs) plus the value of an average hit for that location/type of batted ball, around .5 for an IF’er and .6 for an OF’er (roughly), depending on the location and type of course. So a ball caught (as opposed to not caught) is worth around .8 runs.

If a ball is caught, no other fielder is “docked” any balls/runs. If a ball is not caught, then any fielder who typically (league-wise) catches that location/type of ball at least some of the time, gets docked some number of balls/runs (equal to the percentage of time an average fielder catches that type/location ball).

For outfielders I track fly balls, line drives, and pop flies, although I group pop flies and fly balls together. For IF’ers, I only track ground balls, although there is some evidence that catching line drives is more of a skill than you might think, at least for middle infielders. I also like the way John tracks certain pop flies between the infield and outfield. I do not, but I may in the future (as well as track the line drives).

I don’t do bunts separately, which John does. I treat them the same as any ground ball. One reason I think that he treats them separately is that I don’t think he uses distance as a parameter for the ground balls. I do. So a “caught” bunt would be a short ground ball and even a bunt hit would probably be a short ground ball as well. So I am not sure I need to track bunts separately, although it would probably be better (because of the positioning of the IF for one thing, in potential bunt situations).

I also don’t track good and bad “catches” (scoops and the like) by the first baseman, although that can be done in a number of ways (for example, in the database, STATS indicates whether the first baseman made a good play or not on a thrown ball from another infielder). Again, maybe I will include this in the future.

It is technically not part of UZR, but I definitely track outfielder throws, in the same way that John does (runner advances and runner kills and other assists), although again, I present those results in terms of runs saved or cost above/below average so that it can simply be added to UZR runs.

I also treat errors (both roe and non-roe errors) separately. I am not sure how John handles them. They should be treated separately. Contrary to popular belief, even though the result is around the same, an error, as far as a fielder’s runs saved/cost, is not the same thing as a hit.

Finally, I have a separate rating for turning the double play for all infielders. Basically I split the responsibility 50/50 between the fielder and pivot man. I don’t know if a 50/50 split is correct, but I do it nonetheless. Again, an infielder “turning the DP” is expressed as runs saved/cost and can be added to their UZR’s. Since I track errors and “range” separately in UZR, I sometimes present them separately (to give the reader an idea of a fielder’s “range skill” and “error skill”), although UZR is technically “range plus errors.”

FWIW, a fielder’s error runs involve much more luck than their range runs, and the spread (variance) in runs saved/cost for any number of opportunities, is much smaller for errors than for range.

OK, now on to the question about the parameters.

JH: What factors do you consider when determining the probability of a ball being turned into an out?

MGL: I’m glad you asked! Type (hard, medium, soft, same as John and BIS I think), location (as I said, distance, in typically 30 to 35 feet increments, and 22 pie slices from foul line to foul line), the handedness of the batter (which implicates fielder positioning and sub-speeds within the three classes of speed), the baserunners and outs (which also implicates fielder positioning), and the G/F proclivity of the pitcher (which implicates speed). I hope I didn’t miss any, but I could have.

JH: Do ballparks play a role in your calculation? If so, to what extent?

MGL: Yes, I compute park factors, in the same way that regular offensive and pitching park factors are calculated, using up to 13 years of park data and using a regression formula which includes the physical characteristics and ambient conditions of a park.

It is most important for certain parks and locations within a park, like all of Coors, and left field at Fenway and Minute Maid. Also, some parks have much faster infields than others. For example, the ARI infield is lightening fast, due to both the altitude and the fact that it is hard and the grass is short, and some of the newer breeds of artificial turf (like Nexturf) are just as fast as grass. BTW, it is true that traditional artificial surfaces are faster than grass, but it is not true that there are more ground ball singles on turf than grass (they are about the same). Why is that you ask? More infield singles and bunt singles on grass! But I digress.

I don’t think that John uses park factors. He should of course. It doesn’t make that much of a difference in most parks, but it makes quite a bit of difference in some. They are a little tricky to apply of course. Ideally, for any metric, if we had enough data, we would want to use road data only (plus perhaps a small percentage of home data adjusted for HFA), to get rid of any home park bias. But since we are always limited by the sample size of our data (until players start playing for 50 years or so with little change in talent), it helps to double our sample size by using home data as well, and then do the best we can to park adjust that home data.

JH: Describe the role of fielder positioning in your model and what affect it has on results.

MGL: Good question. Like most of the models and metrics out there (PMR, ZR, Dewan’s Plus/Minus System, UZR, etc.), unique (where a particular fielder likes to play or is directed to play by his coaches, or even is forced to play due to the park) fielder positioning is inherent in the results. We don’t track (no data that I am aware of does) fielder positioning before a play evolves. So really the results of UZR and all of the similar methodologies, as far as I am aware, really measure range and positioning. If one fielder is better at positioning than another, then he will likely have a better UZR even if he has the same or worse range.

For example, they say that positioning is what made Ripken so good. I don’t know, although I have seen him play quite a bit (I don’t trust my eyes very much at all when it comes to evaluating baseball player talent – at least not fielding talent).

The metric cannot separate the two (range and positioning). There is no way for us to know where a fielder is playing based on the data. Actually, I take that back. It is theoretically possible to estimate a fielder’s average position from the scatter plot of the balls fielded and not fielded, but it would be a fairly vague inference and it wouldn’t change a fielder’s UZR anyway.

Most people, myself included, feel that a fielder’s positioning, good or bad, should be part of his skill set. Of course, what if a coach misdirects where a fielder should play, or he only plays in a sub-optimal location because some other adjacent fielder is exceptionally good or bad? That fielder would unfairly get shortchanged in his UZR results. The converse is also true to some extent. If a fielder were correctly playing in an unusual location because his pitching staff has an unusual distribution of BIP’s, his fielding skill would actually be overrated. Some people have suggested that is why I have Swisher rated so good in RF.

As far as positioning due to baserunners and outs, I take care of that in my adjustments or parameters that I discussed earlier. Although Dewan does not do that, it should all even out in the long run.

In the short-run, my numbers are going to be better than his because of all the adjustments I do. The most important adjustment that should be done (besides park factors), as it may not even out in the long-run, especially if a player stays with a particular team for a long time, are the pitcher handedness adjustments. If a fielder plays on a team with a preponderance of lefty or righty pitchers (more than the norm), his numbers in John’s system will be a little “warped.”

JH: How does your model of UZR compare to Dewan’s plus/minus system? To David Pinto’s PMR?

MGL: I think I addressed the comparison with Dewan, and then some. PMR is essentially the same as both systems, although I don’t think that David used distance as a parameter in the OF (maybe he does now). That was an egregious error, and I don’t know why he did it that way. He stated that the “speed” parameter served as a proxy for distance for air balls. That is ridiculous of course (with all due respect to David, who is a great guy and a great researcher). For example, a hard hit line drive in the OF could be 150 feet or 350 feet, depending on the trajectory.

Again, in the long run none of these things are a big deal, but for limited data (1-2 years maybe), they can be. I am not sure off the top of my head what kinds of other adjustments he does or parameters he uses or how many years he uses to establish his baseline probabilities (nor am I sure how many years John uses – he may use one year only). I use 6 years of data to establish the baselines, however I “zero out” everyone’s UZR combined at each position for each year (IOW, a players UZR is always relative to all other players at that position for that year only), for various reason which I won’t go into.

JH: When did you begin working on UZR and how has it evolved/improved over the years?

MGL: I really have forgotten how long I have worked with UZR. 10 or more years maybe. I started out with a simple ZR, which I developed independently from STATS ZR and Sherri Nichols’ Defensive Average (all of them essentially doing the same thing). I was using Project Scoresheet data at the time (I think Sherri was too). At some point I modified my simple “ZR” (I had no particular name for it) and converted it into UZR. That conversion was actually inspired by the old STATS Scoreboard, but I have forgotten exactly how and when.

JH: What modifications have you made to UZR as a result of enhanced data through improved technology?

MGL: Not much really. I started using STATS data about 3 or 4 years ago, rather than the Project Scoresheet (PS) data, although I used to convert the STATS zones into PS zones, which were quite a bit larger (and therefore less granular). I did this only because I did not feel like re-writing my computer routines, which were already set up for the PS data. After much badgering from Chris Dial, however, I decided to use the STATS data, unadulterated. I have also recently improved the methodology and over the years have added the aforementioned parameters and adjustments, and fine-tuned the park adjustments (originally, like Dewan’s system, I had no adjustments at all, except for maybe park factors – I am not sure).

JH: You recently mentioned in another interview that you are working on the UUZR. Can you elaborate on the new metric, what it will incorporate, and how it is different from UZR?

MGL: Boy, you can’t say anything around the sabermetric community without it being noticed and remembered by someone!

Basically two things. One, the subjective ratings that I alluded to when I was talking about the first baseman’s ability to receive throws. STATS provides a subjective rating on every play made, by all fielders involved. Using that would enhance a defensive metric like UZR (or any of them) a lot. For example, much of the data we use is noise. Who cares how many routine plays a fielder makes or how many impossible plays he misses? We really want to know which plays made are great or a little better than average (etc.), and which plays not made could have been made by an average, good, or great fielder (etc.). Unfortunately, the data does not include a subjective “rating” on plays not made. That would be nice, and maybe someday STATS or BIS will provide that, as it is easily done.

The second thing is using the x, y coordinate and smoothing function that I discussed earlier, as well as inferring a player’s average positioning (given certain parameters I guess) in order to separate range and positioning.

To me, that is a UUZR, given the data we have now. Of course once detailed “3D” data (as Tango likes to call it) is available through sophisticated video and other computer technologies installed at the ballparks, we can work on a UUUZR.

JH: The evaluation of defense continues to be a hot topic. With the data that we currently have available, how much closer can we expect to get to perfecting the study of defense?

MGL: Honestly, not a whole lot. We are maybe 90% of the way there. I understand and am sympathetic to the fact that defensive metrics are a lot harder (than offensive and pitching metrics) for the average person (and even some analysts) to get their arms around so to speak. Therefore they are often treated with skepticism and mistrust. Many people think that our methodologies are a “black box” even though almost all of us that have developed these advanced defensive metrics have explained them in detail in various forums (like this one).

Despite the skepticism, I think that we currently do a pretty good job of evaluating and quantifying defense. Not perfect of course and not as good as we do with offense and pitching, but light-years ahead of what was out there before (FA and Range and even Palmer’s Fielding Runs, with all due respect to him, a friend, colleague, and sabermetric pioneer). Books like Dewan’s, which was extremely well-written, will help to legitimize these types of metrics I think.

JH: Who would you say is the most overrated defensive player today in the eyes of the public? The most overrated player in the last 20 years?

MGL: Why Jeter of course! That was an easy one. Griffey, although he was once good, he has been atrocious for the last 5 years or even more. Ditto for Finley. Michael Young of Texas is atrocious although you don’t often hear that (I have even heard that he is good). Grissom (just retired?) has not been good for many years, although he always had a rep as being a good defensive outfielder. Going back some years, the only one that comes to mind (I focus mainly on recent players) is Sandberg. He has never rated that highly (around average I think) in my defensive metrics and of course he is generally known as a very good if not great defensive second baseman. Fielders who hit well and who have few errors (e.g., Jeter, Sandberg) are often overrated. Ditto for those who look “smooth.”

JH: Can you explain your role with the Cardinals and how you serve the front office? Do you consult on more than just fielding metrics and analysis?

MGL: Sure, I consult on everything, although my main focus is on projecting total player performance, including pitching. I have also done work on analyzing and projecting college players for the draft, recommending certain in-game strategies, lineup and bullpen construction, (such as those in our new book), and giving them my opinion (whether they ask for it or not) on player acquisitions, salaries, and even player development in the minor leagues.

JH: What other projects are you working on now or may be working on in the near future besides UUZR?

MGL: My golf game.

JH: Do you make any use out of your law degree anymore?

MGL: Yes, when they come to me for legal advice, telling friends and family to go find a real lawyer and in some cases, recommending one.

JH: Please feel free to expand on anything else you feel is important that we haven’t covered today.

MGL: I think we’ve covered a lot. Thanks for having me. I appreciate it a lot.

baseballdigestdaily / April 6, 2016 / Uncategorized

Harvey’s Wallbangers

In Milwaukee, the Brewers are coming off their first non-losing season since the first Bush administration. Fans are looking away from Gorman’s grill and on to the field for their enjoyment for the first time in a decade. Expectations are high for an extremely young team, so high that you don’t have to listen for long before a Wisconsinite brings up the legend of Harvey’s Wallbangers–the 1982 American League champion, the one unequivocal highlight in franchise history.
For casual fans, memories of the Wallbangers focus, of course, on the stars and the personalities. Their namesake, West Allis native Harvey Kuenn, took over the team in early June, steering the club to a 72-43 finish to take the National League pennant. It was the first of Robin Yount’s two MVPs–his only Gold Glove, as well. The rest of the lineup reads like a who’s who of famous Brewer names: Ben Oglivie, Cecil Cooper, Paul Molitor, Jim Gantner,Gorman Thomas, Don Money, Ted Simmons. Together with a very respectable supporting cast including 26-year-old backup catcher Ned Yost, the Brewers offense did just about everything–wallbanging and more–to crush the rest of the league.
In remembering a great team, the characters become so much larger than life that it’s easy to forget just how good they were on the field. Gorman Thomas, gold-glove centerfielder and Rob Deer All-Star when Rob Deer was still hitting .207 in the AA Texas League, led the club with 39 HRs, often batting sixth. He was one of a seven Brewers with 16 or more HRs, four with more than 28. Not surprisingly, Harvey’s Wallbangers were the 1982 American League team pitchers most hated to face. The Crew put up five-and-a-half runs per game and smashed 30 more homers than the second place team. What’s more, they did all this is a park that was favorable to pitchers.
To get an idea of the magnitude of their attack, let’s look at a game I picked at random: the Brewers in Detroit, Saturday June 19th. One-through-seven, it was the typical Milwaukee lineup of Molitor, Yount, Cooper, Simmons, Oglivie, Thomas, and Howell. Jim Ganter andCharlie Moore each got the day off, giving way to a couple of weaker links on Milwaukee’s bench, Ed Romero and Marshall Edwards. Against Brewer starter Moose Haas, the Tigers would throw Jack Morris, a solid if unspectacular starter for a solid if unspectacular Detroit Tiger team.
Morris may be famous for his win-at-all-costs grittiness and durability, but on June 19th, 1982, he didn’t make it out of the first inning. Handing over the story to
BREWERS 1ST: Molitor walked; Yount homered [Molitor scored]; Cooper singled to center; Simmons singled to right [Cooper to third]; Oglivie grounded out (second to first)[Cooper scored, Simmons to second]; Thomas singled to center [Simmons scored]; LOPEZ REPLACED MORRIS (PITCHING)
Only one extra-base hit–a home run coming from the two spot–but the relentless attack more or less put the game away before the Tigers ever got to bat. Aurelio Lopez didn’t fare much better, giving up four runs of his own before coming out after the third inning. The Brewers managed 10 runs on 9 hits, 4 walks, and one Tiger error while Moose Haas gave up three runs, going the distance for Milwaukee.


The June 19th game is just one example of the most powerful offense of the early 1980s. But Haas’s performance reminds us that, obviously, there was much more to this team. A Cy Young Award winner and two Hall of Famers, just for starters.

Pete Vuckovich
put together the kind of season awards voters love: 18 wins against only 6 losses, an ERA of 3.34–well within spitting distance of the league leader–and of course, he played for a winning team. There’s no question Vuckovich had a great year. Amazingly, though, you can make an argument he wasn’t even the best pitcher on his team, let alone in the American League. Hass, our starter on June 19th, was no more than a solid middle-of-the-rotation guy, but both starter Mike Caldwell and relief ace Rollie Fingers mustered All-Star quality seasons.
Baseball Prospectus’s Pitching Runs Above Average (PRAR) scores Vuckovich at 55–a good, though hardly historical, season. (To give you a reference point, Mark Mulder’s 2005 score was 60, while Chris Carpenter’s was 89.) Mike Caldwell, with his higher ERA but 35 more innings, earned a 58, with Rollie Fingers and his 29 saves coming in at 51. Three solid pitchers to anchor the staff, with guys like Haas, Bob McClure, and swingman Jim Slatongiving the offense a good chance every day.
And then there was Don Sutton. On August 30th, the Milwaukee Brewers woke up with a five-game lead over the Boston Red Sox with 33 games to play. To ensure the division championship and build a stellar rotation for October, General Manager Harry Dalton traded youngsters Kevin Bass, Frank DiPino, and Mike Madden to the lowly Houston Astros in exchange for Sutton, one of the three aces of the Astros staff. (The other two? Nolan Ryan, and Joe Niekro in the middle of a career year.)
The timing of the trade ensured–barely–that Sutton was eligible to pitch for Milwaukee in the postseason. In the meantime, Sutton went 4-1 in seven starts, combining with Vuckovich and Caldwell to lead the Brewers to a 17-11 September. They needed every last one of those wins–the Baltimore Orioles, a game behind the Red Sox back on August 29th, had an even better final month, ending the season in second place by a single game.
95 wins, an MVP shortstop, a Cy Young Award-winning ace, a handful of All-Stars and future Hall of Famers–these are the things longtime Brewers fans get to dream about while watching their young team coalesce on the field this year. It’s still a little early to imagine the Crew in the World Series again, but as a Brewers minor league GM points out, Milwaukee gets a trip to the World Series every 25 years. 1957 with the Braves, 1982 with the Brewers. 1957: winners. That, my friends, might be a pattern you see emerging.

baseballdigestdaily / April 6, 2016 / Uncategorized

Inside Stories and Leadership Strategies From Baseball’s Winningest GM

Atlanta Braves Executive Vice President and General Manager John Schuerholz Jr. was an eighth-grade teacher in Maryland before he was offered and accepted an entry level position with his hometown Baltimore Orioles in 1966.  Schuerholz never looked back as he was given more responsibility and ultimately earned the position of general manager for the Kansas City Royals.  Tremendous success and a World Series win in 1985 opened the door to Atlanta, GA where Schuerholz has assembled the 14-time National League East Division Champion Braves

Built To Win: Inside Stories and Leadership Strategies From Baseball’s Winningest GM
is the story of that success.  The inside stories of ‘Barry Bonds as a Brave for one night’, the Tom Glavine departure, which Schuerholz and Glavine have had to deal with under public scrutiny during the last few weeks, and the chapter named ‘The Diary of a Major League Deal,’ that covered the daily interaction between Schuerholz and Tim Hudson’s agent, are incredibly revealing and detailed.  The reader is taken into the world of the Atlanta Braves GM who is running, arguably, baseball’s most successful franchise.


The publisher (Warner Books) obviously wanted the Barry Bonds story, which is Chapter One, and the Moneyball rebuttal in Chapter Two to be the first things readers scan after the foreword by Bob Costas.  The ‘inside stories’ span the entire book (the GM’s career)…things like evergreen contract clauses, the Moneyball approach to building a roster, and players Schuerholz acquired with off-the-field issues like Darrel Porter and Vida Blue from the Royals and John Rocker from the Braves.  Great stories like the Baby Braves, the re-discovery of Julio Franco, and Andruw Jones negotiating his own contract extension a few years ago fill the front of the book while the ‘leadership strategies’ and the stories and examples that accompany them mostly fill the rest of Schuerholz’s entertaining memoirs.  Some of the really juicy details from most of the stories are left out only to protect the players.  If you have followed the Braves and Royals over the years you may be able to figure them out!
There are some jabs at the power agents and the players association on several topics, including the Alex Rodriguez deal.  Hey Braves fans… Schuerholz had the second highest offer on the table for A-Rod at $126 million.  That’s exactly half of what he received from the Texas Rangers.  Schuerholz wasn’t accusing anyone, but if the owners and GM’s can’t compare the contract demands of players, or what is called collusion, then why can the agents and the players compare contract offers?
“Another case where an agent got past knowledgeable baseball people and got to an owner,” said Schuerholz.  “Agents talk among themselves and with the union, sharing negotiating information all the time.  That’s allowed! What a system!”
The strength of the Braves minor league system has played the greatest role in the success of the Braves under John Schuerholz.  Schuerholz respects the opinion of his minor league coaches and scouts and tells dozens of stories that relay that fact throughout Built To Win.  The reports from those scouts led to the Raul Mondesi signing in 2005 and the J.D. Drew signing the year before.  It also led to last season’s spring training trade for Jorge Sosa which stabilized an injured Braves rotation at the time.  But it’s not all about the Braves.  Great ‘inside stories’ from his days with the George Brett led Kansas City Royals are classic.
Schuerholz talks about Bo Jackson being a freak of nature in a baseball uniform, Deion Sanders playing two professional games in one day, and how the Braves signed Terry Pendleton in 1992.  People questioned the signing at the time, but later that season Pendleton would be named NL MVP.  It seems as though Schuerholz could go on forever with each story, but they are all edited down nicely, and they are all memorable.
Schuerholz graciously thanks all of his former bosses, especially the one who gave him the first big break in his career, Lou Gorman.  He goes into detail about how he broke into the league as an administrative assistant for the Baltimore Orioles by writing a letter to the team.  He goes on to give great examples of what he learned from his mentors on his way to becoming one of the most successful GMs in the league.
Schuerholz takes tremendous pride in his ability to sit and listen to his scouts, managers, and other assistants.  He often credits current manager Bobby Cox, former pitching coach Leo Mazzone, and Jim Fregosi, a special assistant to Schuerholz, for giving expert advice.
Schuerholz uses several stories from his time with the Royals to show just how much the game has changed over the last three decades.  He despises agents and directs them all to Vice President/Assistant GM Frank Wren. He only deals with them when he has to.  Who could blame him after the A-Rod deal?
After reading much of the book, the reader may wonder how on earth anyone can deal with such change and diversity in their daily activities, much less in their job. “I doubt there is a general manager of anything who has to deal with change more than a baseball general manager,” Schuerholz says.  Schuerholz has always learned on the fly with things like free agency, arbitration and, in his case, having to eliminate $20 million from the payroll before the 2004 season.
Maybe if he had known the challenges that were to come with the Braves, the decision to leave the Royals would have been even tougher than it was.  Schuerholz left a good situation working for good management (he worked side-by-side with a young Rush Limbaugh too) to go to Atlanta which was then the laughing stock franchise that some say the Royals are now.  Many of his friends at the time let him know about it too!  “What a shame.  Schuerholz was such a talented guy, but now he has lost his marbles.”
The Schuerholz children were born in KC where John’s wife was also raised.  It was not an easy decision for him to leave that city.  But he had a vision for the Atlanta Braves and talks about that vision in detail throughout the book.  In his early days in Atlanta, Schuerholz tells stories of how he prepared for every staff meeting to inspire his employees.  “Maybe it’s my belief in the Pygmalion Theory, the self-fulfilling prophecy, that if you believe so strongly in something and you have capabilities and a strong work ethic, you can achieve those things,” Schuerholz said.
When Schuerholz pens quick poems and recites motivational credos (some of which are on his office wall), he really comes across as the grade school teacher that learned a lot from his father, brothers and his grandfather back in Baltimore, MD.  His family was well known in the area for their athletic prowess.  He says his grandfather Will, who played in the minors and was an amateur basketball player, was known as the ‘Bob Cousy’ of Baltimore.  But baseball is where the 150 lb. John Jr. says he succeeded the most.  “My self-confidence and competitive nature always exceeded my physical stature.”  In fact, he was presented with the Athlete of the Year award at Towson State in 1962.
There are so many stories that could have changed the course of his career in baseball.  Schuerholz was offered the job as Farm Director for the New York Yankees in 1975.  He was young and felt like five years warranted a promotion, so with the blessing of Gorman, Schuerholz interviewed and negotiated his own deal to the Yankees.
“You’ve made the biggest mistake of your life,” said Gorman.  “Can you give me twenty-four hours?”
Schuerholz eventually decided to stay on board with the Royals, and he should probably thank Gorman for keeping him there, since it might have been the single most important decision of his baseball career.

baseballdigestdaily / April 6, 2016 / Uncategorized


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baseballdigestdaily / April 6, 2016 / Uncategorized