“Smart Baseball” Is a Baseball Statistics Education in Three Parts

Given how long he’s been focused mainly on scouting prospects in his job at ESPN, one can sometimes forget just how well versed and influential Keith Law has been to the sabermetric community through the years. But we shouldn’t, and his new (and first) book, Smart Baseball: The Story Behind the Old Stats That Are Ruining the Game, the New Ones That Are Running It, and the Right Way to Think About Baseball, serves as a reminder of his deep well of knowledge. While the whole book may not be of interest to loyal readers of sabermetric sites like FanGraphs, Baseball Prospectus and this site, there is most certainly interesting material for even the most strident follower of sabermetrics.

As with many books that are meant to appeal to as broad a base of potential customers as possible, this book is tasked with educating those who are not yet sabermetrically inclined while still teaching something to those who are. It is a fine line to tread, and Law does the best he can, offering good nuggets of info and good examples to use when striking down the narratives of the past in the chapters that will be more mundane to the devoted sabermetric reader. Conversely, he does a good job of explaining core sabermetric concepts without getting bogged down in too much math that is likely to turn off the more casual baseball fan.

Law lays out the book in three parts. Part One will be least appealing to loyal readers here. If you’re familiar with Law’s work or his tweets, you can probably guess what the theme of this section, titled “Smrt Baseball,” is.

In case you’re not familiar with why Law would leave the “a” out of “smart” there, observe:

This first section is filled with lessons that most sabermetric readers learned a long time ago. Chapters focus on individual statistics that are no longer in vogue in the sabermetric world, such as pitcher wins, runs batted in, fielding percentage and saves. This part of the book takes up the first third, and it is where Law is at his snarkiest. It is also where the book is likely to have the greatest impact generally. While many sabermetric readers pay for ESPN Insider and form a portion of Law’s audience, the reality is that the majority of people likely know him from his television appearances on the Worldwide Leader, and as such, this section is aimed at them.

Examples like Bob Welch winning the 1990 American League Cy Young Award over Roger Clemens and Dave Stewart is one example Law leans on, as well as Barry Bonds losing the 1991 National League Most Valuable Player Award to Terry Pendleton. The latter example is at the end of the first chapter, titled, “Below Average: The Fundamental Flaws of Batting Average.” To close out that chapter, Law explains why some traditional stats are so hard to kick, and lays out what is essentially his mission statement for Part One — helping fans get past what they’re used to in order to arrive at a more enlightened place.

So if the appeal of batting average as the lord of hitting stats isn’t accuracy, or ease of calculation, then what is it? In many ways, the adherence to batting average isn’t easy to explain, because it just isn’t that logical. Batting average is emblematic of how the weight of baseball history can be the largest impediment to success on the field. The emphasis on batting average when smarter stats are out there embodies the false dichotomy we’ve seen in baseball coverage over the last fifteen years, whether it’s pitched as “scouts versus stats” or traditional versus modern: the writers and fans who profess to disdain statistical analysis in face rely very heavily on their own statistics — the ones they’ve used their whole lives. These statistics, like batting average, pitcher wins, and others I’ll cover, are simpler to calculate or count, but they give us an incomplete or sometimes plain inaccurate picture of what a player did to help his team. Yet because they’ve been around forever, many fans don’t want to let them go.’

Part Two, titled “Smart Baseball” (adding back in the “a”) is then naturally focused on the stats the sabermetric community now uses in place of those Part One statistics — on-base percentage, wOBA and wRC, WPA and WAR, among others. Depending on your mileage as a sabermetrician, this may serve as refresher rather than new knowledge as well, though I would submit that this bit of refresher is very valuable. After using certain statistics for so long, it can be easy to forget why they are used, how they came to be and what goes into them. Law lays that all out in an easy-to-understand format, tackling one statistic or subject per chapter.

The subject of defense actually does come up twice in Part Two, both in relation to pitching, and then again in a later chapter on its own. The first time, in the chapter titled “ERA and the Riddle of Pitching Versus Defense,” Law explains the issue the sabermetric community faces in trying to determine where to place credit or blame for balls hit into the field of play — with the pitcher or the defense? The 2015 NL Cy Young Award vote is used here to illustrate the difficulty in determining what the right approach truly is. Later, the chapter entitled “The Black Box: How Baseball Teams Measure Defense Today” tackles defense singularly.

Part Three delves into Hall of Fame voting, how statistics help scouting and the future of sabermetrics, most notably when it comes to Statcast. Titled “Smarter Baseball,” this section is where the real meat on the bone is for devoted FG and THT readers. Unfortunately, it’s about 30 pages shorter than the other two sections — in particular, I was hoping to read more about the meld between statistics and scouting — but what is here is all great stuff.

As he weaves his way through the book, Law touches on all the familiar books, authors and articles one would expect. Books name checked include Baseball Prospectus’ Baseball Between the Numbers, Elias Sports Bureau’s Baseball Analyst books, SABR’s Baseball Research Journal, Bill James’ Historical Baseball Abstracts, Michael Lewis’ Moneyball, Jeff Passan’s The Arm, Andrew Dolphin, Mitchel Lichtman and Tom Tango’s The Book, and John Thorn and Pete Palmer’s The Hidden Game of Baseball. Other people, institutions or articles name checked include Rob Arthur, Clay Davenport, John Dewan, Mike Fast, Gary Huckabay, Jay Jaffe, Jonathan Judge, Harry Pavlidis, Alan Nathan, Andrew Perpetua, Mike Petriello, Cory Schwartz, Joe Sheehan, Dan Turkenkopf, Keith Woolner, the 1985 “hot hand” study by Thomas Gilovich, Robert Vallone and Amos Tversky, Mitchel Lichtman’s “UZR Primer,” George Lindsey’s “An Investigation of Strategies in Baseball,” Matt Swartz’s arbitration projection model at MLB Trade Rumors, John Updike’s New Yorker essay “Hub Fans Bid Kid Adieu,” Voros McCracken’s “Pitching and Defense: How Much Control Do Hurlers Have?” piece at BP, Baseball-Reference (and its invaluable Play Index), Baseball Info Solutions, Baseball Prospectus, Beyond the Box Score, FiveThirtyEight, MLB.com, Saberseminar, Sports Illustrated, Stats Inc., The American Sports Medicine Institute, and of course, FanGraphs and The Hardball Times. And those are just the ones I made note of. Also, this list doesn’t count all the front office executives that Law interviewed for the book, of which he interviewed many.

Those front office interviews are one of the things that help the third part of the book stand out from the first two parts. While baseball executives rarely go into specifics, Law was still able to glean some great info. Here’s one I found interesting, on the challenges of managing data. From the chapter “The Edge of Tomorrow: Where the Future of Stats Might Take Us”:

One longtime executive who’s overseen the construction of analytics departments for multiple teams put the opportunity this way: “Anytime there’s a new data stream, organizations face the question of when and how to integrate the new data into their decision-making processes. Organizations that go too quickly might rely on data that is inaccurate or compromised in some way. (We saw that time and time again with early defensive data.) Organizations that wait too long might fall behind and find themselves at a competitive disadvantage. Organizations that rely too much on a single new measure might be underemphasizing other important variables. Organizations that don’t factor the new data enough in their mix might be missing out on the benefit of the breakthrough. So, generally, I think the next big opportunity is not in a single new data stream or field of research. Instead, it lies in applying new data at the right time and in the right proportion with other variables to best predict future performances.”

No easy feat, especially these days, when the data is, as one front office employee described it to Law, “continuous.”

Elsewhere in Part Three, Law gives us one of the better examples I’ve seen on the difference between command and control. People always get tripped up on the difference between the two, mixing them up or just plain getting it wrong, so it is always nice to have a succinct comparison. From the chapter “No Trouble with the Curve: How Scouting Works, and How the Statistical Revolution is Changing It”:

One of the most common questions I get from readers is about the pitching terms command and control — what they mean or what the difference is between the two. Defining control is simple: it’s the ability to throw strikes, period. It doesn’t speak to the quality of those strikes, but simply to throw the ball over the plate within the strike zone, middle, edge whatever. … Command, roughly speaking, is the ability to put a pitch where you want it, to make it do what you want it to do. I think of it as ownership of the pitch: if it doesn’t land where you needed it to land or break the way you needed it to break, you didn’t command it. Control is more tangible and rarely goes away without warning, but command wavers.

Smart Baseball is well worth your time, whether you’re a seasoned sabermetrician, or you are a more casual fan who wants to learn what all the fuss is about. It’s a baseball statistics education in three parts, and whether you think of yourself as a Part One, Part Two or Part Three kind of fan, the book has plenty of good info in it, and Law’s years of experience and knack for organization help give the book a learned, clean feel.