“Scientists don’t immerse themselves in particulars only for the grandiose (or self-serving) reason that such studies may lead to important generalities. We do it for fun.”
–Stephen Jay Gould, “Opus 100”, reprinted in The Richness of Life: The Essential Stephen Jay Gould

Twenty-five years ago, paleontologist, evolutionary biologist, and historian of science Stephen Jay Gould wrote his 100th monthly essay for Natural History magazine titled, appropriately enough, “Opus 100” (Opus being the Latin word for a single work or composition). In that column, Gould indulged his personal passion for the Bahamian land snail Cerion by describing the several puzzles that Cerion presents to evolutionary thinking, and how his own research had shed some light on such knotty problems. Gould would go on to pen exactly 300 essays, stretching from 1974 through January 2001 in his series titled “This View of Life” (from Charles Darwin’s statement about evolution in the last paragraph of the Origin of Species: “There is grandeur in this view of life…”)–a streak that I think even Joe DiMaggio himself could admire.

Well, our little endeavors to illuminate the history and workings of baseball here at Baseball Prospectus may not rival the larger themes that Gould wrote about, but still I think his quotation at the start of this column applies in spades to those of us who have attempted to shed some light on the game that we love. By now, you probably know where this is going, and you’d be right in guessing that this article marks the 100th edition of Schrodinger’s Bat, a column that began on March 30, 2006 and has run (almost) weekly since (with a few other contributions sprinkled in along the way). In the same way that Gould indulged his choice of research subject in his Opus 100, today I’ll run down my personal favorites in the series.

Before getting started, this seems a perfect opportunity to once again thank the many readers who have questioned, prodded, and enlightened me during the past two years. So in no particular order, here is my top ten list.

The Schrodinger’s Bat Top 10

  1. Tilting the Playing Field. This column was published on August 30, 2007, and it revisits one of my favorite themes, one that Gould also explored in documenting the increasing level of play in major league baseball. Although this was by no means a new topic to sabermetrically-inclined readers, the approach of using pitcher hitting relative to position players based on a concept of natural selection (pitcher hitting not being a trait that is selected for) to create a “level index” was one I hadn’t seen dealt with in detail before. The column does just that, by inverting the relative production and applying a moving average in order to create an upwardly sloping line that starts at an index of .50 in 1876 and culminates in 1.00 at 2006. I then use the level index in conjunction with Keith Woolner‘s WX framework to level the playing field a little and look at how seasonal and career numbers can be adjusted using this framework.

    While these sorts of analyses ultimately turn out to be little more than thought experiments, because of the many other differences that cannot be quantified, they appeal to me (and hopefully to some of you) because of their broad scope in historical terms, conceptual power, and their ability to sometimes turn the conventional wisdom upside down.

  2. Simple Fielding Runs v1.0. A topic that I’ve recently been interested in is the creation of a defensive metric based on Retrosheet-style play-by-play data that does not include hit location information. The idea occurred to me one Friday night, and several hours later I had a working system that appeared to yield interesting results. As regular readers know, that system underwent several modifications (in no small part because of your feedback) and finally I published version 1.0 of Simple Fielding Runs (SFR) on January 24, 2008. That column describes the system for infielders (the outfield system was published a few weeks later after being totally revised once) and compares SFR with Ultimate Zone Rating (UZR) and Baseball Info Solution’s Plus/Minus System.

    Although the system has since been expanded so that it is able to be run on data sets that are not as complete as the 2003-2007 and minor league data we have, it probably is about as accurate as it can get (for infielders anyway) given the limitations of the data. For the software developer in me, the interest in projects like these not only lies in the results (just how bad a fielder was Dick Allen?) but the process (actually the code) through which those results are generated.

  3. Visualizing Pitches. All readers interested in the cutting edge of baseball analysis no doubt have a sense of the importance of the PITCHf/x data made available by as a part of their Gameday system. There are simply an unending number of questions that can be studied with this wealth of new information, and in this column I’ve done my best to dig into a few of them. In this particular column published on August 23, 2007, I explored the three velocity and three acceleration data points reported in the PITCHf/x data to create three-dimensional graphs of particular pitches, as well as pitcher repertoires. I also looked at the differences in Barry Zito‘s and Rich Hill‘s curveballs, Derek Lowe‘s and Roy Halladay‘s sinkers, and even the full complement of Daisuke Matsuzaka‘s pitches. Even though I haven’t used the technique very often, I still feel that visual representations of a pitcher’s repertoire (the “Platonic types” of his arsenal), especially when able to be manipulated by the viewer, are a helpful way of understanding how pitchers compare to one another.

    As hinted at, although the experience of being able to rotate these 3D views was a bit lost on readers since in the article we could only show static views, it was great fun and an interesting challenge to create the software to plot the pitches and rotate the display.

  4. Wins and the Quantum. Very early on–in fact in my second column on April 6, 2006–I explored Keith Woolner‘s Win Expectancy (WX) Framework as described in the Baseball Prospectus 2006. For me, applying Woolner’s work and actually having it published on BP was perhaps my biggest thrill, since I had been a fan for several years, and greatly admired Keith’s work, then and now. But aside from that, it also gave me an opportunity to put the title of this column (invented by Will Carroll, I should add) into context and describe the original controversy in quantum physics that spawned our play on words. Since that column, I’ve occasionally tried to draw parallels between issues in science and those in baseball, admittedly being more successful in some instances than in others.

    In applying WX at both the level of seasons and careers without considering the timing of events that play-by-play data affords, it allows us to remove those factors that get a lot of press but that ultimately don’t reflect much of a repeatable skill. This approach was also revisited when discussing the “clutch” performers of 2006. And of course it also puts everyone on a level playing field within their own context allowing for cross-era comparisons and showing us that (through 2005 anyway) Babe Ruth still led Barry Bonds, 117.4 wins to 108.7, when only their offensive contributions were considered.

  5. Science and Art of Building a Better Pitcher Profile. We’ve already touched on the wealth of information that can be garnered from PITCHf/x, and perhaps the first column I wrote that dug into what that data looks like for individual pitchers was the one I wrote on June 14, 2007 on “King” Felix Hernandez. Hernandez was a case study of sorts for developing a profile that encompassed four basic questions: what does he throw, when does he throw it, where does he throw it, and what happens when he throws it? All of those questions revolve around the identification of pitch types, so in that column I showed what has become a canonical graph of pitches grouped by horizontal and vertical movement by velocity, and discussed how that information can be used to identify pitch types. In addition to creating the profile, I also discussed at a more philosophical level the value of classifying pitches and the potential for doing so for every pitcher, which other analysts quickly began and which MLBAM is now doing as well.
  6. The Myth of the Golden Age. This column published in January of 2007 formed the basis for the first column in our list and, appropriately enough, explored the chapter in Gould’s book Full
    House: The Spread of Excellence from Plato to Darwin
    , in which Gould enumerates the arguments that lead one to believe that the level of play has increased over time. In the column, I update his primary quantitative argument (coefficient of variation in batting average over time) and then plant the seeds for that next column by discussing the various ways in which the rising tide has been measured in the past, taking a first stab at doing so by the relative performance of pitchers versus position players.
  7. The Whole, the Sum, and the Parts. As many readers know (and some only too well), the measurement of the impact of baserunning has been a favorite topic of mine for several years. When I began writing for BP in the spring of 2006, I also began the process of revamping and extending the existing baserunning framework I had previously developed. In a series of seven articles in the summer of 2006 that culminated with this one published on September 14, the framework grew to include advancement on hits, ground-ball outs, fly balls, stolen bases, and pick-offs, and more recently passed balls, wild pitches, and balks. Those numbers are now a part of BP and were also applied to minor leaguers and published in Baseball Prospectus 2008, along with an essay that summarizes the methodology used.

    For me, studying the particulars of baserunning, besides just being fun, does lead to interesting generalities, because it allows us to put baserunning’s impact into its proper context. Whether it’s measuring the impact that a baserunner can have in a full season, comparing the relative importance of the various kinds of advancement events, or developing an aging curve for baserunning that can be applied to forecasting, for my money nothing is more interesting than shedding a little light in a corner of the baseball world that was previously pretty dark.

  8. The Curious Case of Mark Teahen. Just what goes into making a seemingly mediocre player a key contributor overnight? I suppose that’s an age-old question that many a general manager has pondered. While analysts like myself typically try and concern themselves with larger trends and associated large sample sizes, it’s always interesting (as Marc Normandin proves repeatedly here at BP) to see if we can drill down and get a glimpse inside that transformation. In this column, published on August 31, 2006, I explored the ups and downs of the Royals‘ Mark Teahen who was having a superb 2006.

    The approach used is one that is time-honored in sabermetric circles: finding comparable players, and using them as a proxy for how the player in question might develop. While I still believe the targeted study that was done did indeed indicate that Royals fans had reason to be cautiously optimistic that Teahen’s increased power was not a mirage, this column is a testimony to the inherent variability in the game and the uncertainty that operates at the level of the individual, as Teahen regressed significantly in 2007. On the other hand, it is precisely those unknowns that make the game endlessly fascinating in our capacity as fans.

  9. Physics on Display. Back on the subject of PITCHf/x, one of my earliest columns on the subject dealt with the physics involved when a baseball moves through the air, and how the system captures the effect of drag and spin and even captures differences in ballparks. While occasionally receiving some gentle corrections from Alan Nathan, the physics of baseball has always been of interest to me and I suppose I’m still a little amazed that the PITCHf/x system is able to measure the effects introduced by the various contexts in which a pitched ball is thrown.

    As you might imagine, since the article was published in late May of 2007, it did not have the benefit of a large data set to back it up, and so I revisited some of these topics in a column last October, and at that time measured the difference by time of day as well. This system, and the concept of ball tracking in general, will serve to keep us busy for quite some time to come.

  10. The Burgess Shale and Other Weighty Matters . This column was originally published in February of 2007 and was actually a continuation of a previous column that appeared a couple of weeks earlier on the topic of triples and how their trend towards extinction may have been fueled by increasing body mass index. In this installment, I looked at the historical forces that might have been at work in contributing to a decline in stature amongst ballplayers in the second decade of the twentieth century. After reviewing several competing theories I landed on the sharp increase in the number of players used and their relatively young ages during that time as the likely cause of the apparent decline.

    After exploring the reasons more players were used (experimentation in pitching patterns, pinch-hitters, and specialization such as pinch-runners and platooning) the column finishes by drawing an analogy to the world of paleontology and the reinterpretation of the paleontological treasure trove of the Burgess Shale in the 1980s. I’m always a sucker for a good analogy (and it is what prompted me to include the column here), but, more importantly, that short discussion is a great illustration of how powerful concepts (in this case the inversion of the assumption of increasing diversity) can sometimes be seen in what at first might seem to be the smallest of details.

And Now For Something Completely Different

To be sure, I’ve had a ball analyzing and writing about baseball over the past two years here at BP, and previously at THT, but, as they say, all good things must come to an end. That isn’t because I’ve run out of topics to explore, but is instead because I will be leaving Baseball Prospectus to join the front office of the Pittsburgh Pirates to become their Director of Baseball Systems Development. In that capacity I’ll be assisting the excellent staff–including Kyle Stark, Bryan Minniti, Greg Smith, and Joe Delli Carri, under the direction of General Manager Neal Huntington–in building systems to support and inform the decision-making process of the baseball operations staff. All of those individuals mentioned, and many others, have made me feel more than welcome, and I’m thrilled to start the process of integrating the array of quantitative and qualitative information in a way that makes both even more instructive.

Of course, I’m also more than a little sad to be leaving BP, where I’ve had the pleasure of working with such supremely talented individuals and interacting on a daily basis with an informed and passionate readership. To both the staff at BP and to you in the audience, I can only say thank you, and wish you all the best.

Thank you for reading

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Dan Fox


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