“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.
If it’s written with Law’s signature snark I can’t imagine his book will change many people’s opinions. It almost sounds like a book without an audience. It’s elementary for fangraphs readers and the like and dismissive of people who are still counting RBIs.
I’m afraid you’re right. ESPN published a snipped about sac bunts recently (I found it rational and nuanced), and the comments fell roughly into 3 buckets:
90% “this garbage is why no one reads Keith Law. Everyone knows more about baseball than he does!”
5% “I clearly only read the headline.”
5% “Yeah, this makes sense.”/ “Wow these comments are stupid.”
The 90% I think were mostly offended that Law was making fun of them throughout. Not sure he’s going to get many scouting/sabermetric independents.
It is indeed written with his usual snark. He repeatedly calls tradional stats “stupid”, implying that he is oh-so-smart. Yes, batting avg. is flawed, as are RBIs, etc, but do you have to be so smug & condescending, Mr Law?
I’ve only read the “free sample” thus far, as I ponder whether or not to shell out $$$ to Mr Law, even though the subject matter is of interest to me. Why, why, why is it Mr Law, that you always act like you’re the smartest person in the room?
The snark is at a minimum. Instead, he goes through the history of the old stats and explains why they suck. The tone is definitely different than his Twitter or chat persona.
IMO, the sac-bunt excerpt on ESPN was lazy, flawed reasoning in the service of a point that should be pretty easy to prove. I just don’t enjoy his writing any more.
Even though I agree with most of what he says, I find Law smug and arrogant. He seems to totally lack any comprehension as to why people enjoy the old stats and why baseball history has such a hold on people. I don’t think I’m a hidebound purist unwilling to accept new ideas, but, jeez, why can’t he just let people enjoy baseball the way they want. I am astounded at the seeming need for many sabermetricians to act a if proper baseball thinking is necessarily for a good life. It’s just a game. Personally, I believe in the new analytics, yet at the same time, I enjoy the history behind things such as pitcher wins. I realize it’s a flawed concept for analyzing pitcher performance, but it still brings back a lot of fond memories in thinking about, say Denny McLain’s 30 win season. These are important parts of baseball history that Law would seemingly relegate to the trashbin of history.
Having said that, I think the anti-intellectualism that seems to attach to anti-sabermetrics is disturbing and reflects a close-mindedness that goes far past sports. So, as this suggests I am torn. But I think Law’s snarkiness and condescension turn off those other than his existing acolytes.
100% concur. The title of the book says it all really “The right way to think about baseball”. People do not like being told what to think and that’s something he hasn’t yet grasped. I find his scouting and front-office insights fascinating, but the condescension is tiresome.
Dear Mr. Schneider,
You are my kind of baseball fan. You know your history and you know how to express yourself.
When I go to the occasional game I will, if not distracted, try to keep score – using the form provided in that day’s official program. I get real joy by just chronicling a game in the form that is both simple and telling – be it on paper, or better still, being stored in my memory bank.
An example, what stat would possible cover how a hitter ‘stretched’ a double into a single just so he could say that he ‘hit’ for the cycle that day!? (That was Kelly Gruber of the Toronto Blue Jays at Exhibition Stadium…I was in the stands on the 1st base side…we won the game, whew!)
May we, or our like, continually cross paths wherever the great game is played.
Sincerely,
Ken
Ken,
Thank you; I appreciate the kind words. I also enjoy scoring when I go to the games, although I no longer have the patience to do it when I’m watching on TV. When I was a teenager growing up in Braves territory, I would score 100 or more games a year, listening on radio. It was (and is) a great way of staying in the game. I still remember the details of games played 45 years or more ago.
As I said, I like sabermetrics as a way of better understanding the game, but, as you suggest, there are parts of the game that cannot really be quantified. Or, more precisely, why do we need to quantify them?
Best to you, sir, and enjoy the games.
Marc
I’m a lifelong baseball fan approaching 60. I stopped watching ESPN, moved to mlb network and now simply get my baseball fix on the web mostly from the sites of teams I follow.
I find many national game broadcasters including some at ESPN simply don’t follow the teams they are broadcasting which wouldn’t be too bad except I’m forced to conclude they feel obligated to fill broadcast silence with insights into a team and it’s players which only corroborated they don’t follow the team and don’t know what’s going on with its players. I watch every game my team plays so I at least know the basics. This amounts to fake news.
As for sabermetrics something is gained and something is lost. As a statistician I love it. I have stopped attempting to stay on top of the latest developments because I just want to enjoy the game. Baseball is so subtle. A team can have the best spray charts and subsequently place their fielder’s in the exact spot but if a pitcher fails to locate it is all for naught. Warren Buffett is famous for being the best investor ever and his great insight is “intrinsic value” which is sometimes impossible to quantify such is the case with the name “coca cola” . At face value Terry Pendleton shouldn’t even be mentioned in the same sentence as Barry Bonds, right? How many actually saw Pendleton play day in and day out? Defensively, the hot corner is infinitely more important that left field. I never saw a third baseman run full tilt as far as you can go into the left field corner, catch the ball over his shoulder, turn and fire a strike to the plate to nail the runner who had tagged up. I saw Pendleton do it multiple times, most importantly in the world series.
Here is what has disappeared from today’s game, partially if not totally due to the loss of independent thinking by players because they need to be positioned like chess by a manager’s analytic team. And also due to the the sabermetrics that drive the next big raise. Stolen bases. Hit and run. Bunting. Fielding. Outfielders long throwing runners out. Pitchers being able to pitch as opposed to heaving the ball as fast as they could. This has led to more Tommy John surgery. Players like John Tudor probably would never make the majors today but Tudor knew more about pitching then most pitchers filling roster spots today. Giving yourself up to push a runner over. In many cases cut off men can’t throw accurately.
Regarding Pendleton over Bonds. I think a lot of it stemmed from the fact that Pendleton was perceived (correctly) as the best position player on a surprise playoff team, as well as that a lot of voters just didn’t like Bonds personally. Pendleton didn’t have as good of a season as Bonds, but I don’t think that he was a particularly bad choice. It was a rather average season for Bonds. Bonds was also capable of playing center, but moved for Van Slyke – pretty much the definition of putting one’s team above oneself.
The irony is that Bonds shouldn’t have won the MVP that year, rather it should have gone to Pendleton’s teammate, Tom Glavine, who led the league in rWAR, ERA+, wins, and complete games, while being in the top five in nearly every other pitching category. He was also a good hitter for pitcher, worth 0.7 by Fangraphs or 0.8 by baseball- reference. But this would have taken looking at Glavine’s ERA+ rather than FIP, acknowledging that Glavine consistently outperformed FIP over his career, as well as that a pitcher was the best player in the league.
Side note: this is also an example of my theory that most times there is a controversy over an undeserving MVP, whether for a bad team (ARod in 2003) or for traditional stats (Morneau in 2006), the MVP should have gone to a pitcher who, while pitching for contender, was either the best player in the league (Johan Santana in 2006) or close to it (Pedro in 2003)
These comments are indicative of so many just willfully ignoring the way the game has changed. No one, not one single person, is saying you can’t enjoy Batting avg or RBIs. It’s just that analytics and new found ways of analyzing the data in the game. It isn’t that he thinks he’s smarter than anyone (I mean, he is, he went to Harvard and MIT, he’s a fucking brilliant guy), but that he is saying that RBIs, AVG are a one dimensional way of looking at the game. The point of baseball is to get on base and score runs. Most of the new stats simply share how to do that in a more strident manner. It clears out all the noise and zeroes in on the more singular forms of data. That’s important and vital. Basketball does it as well. If you CHOOSE not to want to share in that knowledge then don’t -say it’s his fault. Yeah he’s snarky. So don’t follow him. Life is about choices. Stop bitching about YOUR choices and just change. Instead you fill up comment sections and whine about how you’re old and don’t get it.
Bob,
You are making a strawman argument here. I don’t see any comments here that are anti-sabermetric or even anti-Law, except to the extent that he turns people off with his attitude. I also don’t see anyone saying they don’t want to share in the new knowledge. No one is saying they are old and don’t get it. I certainly didn’t. But the implication of the title of his book (which, admittedly he might not have chosen) is that people who still look at traditional statistics are, at the very least, not watching the game the right way.
You seem to object to people not genuflecting before Law. I have a lot of respect for Law’s knowledge of baseball and the insight he brings to new ways of analysis. I also think he’s an arrogant, sanctimonious jerk-and not just about baseball. At least that’s the way he comes across to me. Maybe he is a nice guy in person.
If his goal is to convince people of the value of sabermetrics, he would be more persuasive if he wasn’t so snarky. That’s all people are saying. Obviously, there are people that simply don’t buy into the advanced analytics and resent the new stuff. Those people are probably never going to be convinced. But that’s not the people on this site. But even people that agree with Law find him arrogant and condescending. As for going to Harvard and MIT, whoopee shit; lots of people like that decided that we should fight the Vietnam War.
I think that Marc Schneider hits it on the head. Instead of converting old school people to his way of thinking, Law annoys them with smugness and arrogance. That approach is never going to work if your goal is to convince people to come over to your side.
There is also no one “right way” to think about baseball. People approach the game in different ways. I enjoy baseball through storytelling and the aesthetics of the game on the field, while still having a basic appreciation for Sabermetric statistics. For me, the numbers supplement my enjoyment of the game, but I don’t want them to become an overload or an avalanche of information.
For me, that’s how I enjoy the game.
I’m afraid you’re right. ESPN published a snipped about sac bunts recently (I found it rational and nuanced), and the comments fell roughly into 3 buckets:
90% “this garbage is why no one reads Keith Law. Everyone knows more about baseball than he does!”
5% “I clearly only read the headline.”
5% “Yeah, this makes sense.”/ “Wow these comments are stupid.”
The 90% I think were mostly offended that Law was making fun of them throughout. Not sure he’s going to get many scouting/sabermetric independents.
What has always separated Bill James from the guys who came and went like Mike Gimbel, Don Malcolm, Joe Sheehan and now Keith Law is that James could flat out write. If you think there are a lot of people who resist sabermetrics now, remember that James was basically the lone voice in the wind introducing concepts and statistics 95% of baseball fans hadn’t even considered and that MLB either laughed at or vehemently resisted. And yet, the people that he influenced have gone on to basically reshape how baseball is understand and played.
Nowadays it seems as if the field of sabermetrics is filled with writers and statisticians who were influenced more by the people who were influenced by James than by Bill himself and I read more and more about how James was “good in his day but he should step aside now.” The trouble is that there are too many sabermatricians writing today that either don’t know how or feel it’s beneath them to actually try to persuade and instruct their readers, let alone engage them.
I was hoping that Law wouldn’t let his often annoying snark seep into this book but this review and the comments from those who have checked it out are not promising.
Well said about Bill James. He could be pretty snarky himself, but he could really write, in a way that was both explanatory and engaging; he made the stats tell a story. There are many other good stat-minded writers, but I’ve yet to find his equal.
I was not sure that Pendleton’s MVP was a mistake then, and I’m not sure now. rWAR has Bonds ahead 7.9 to 6.1. But offensive WAR is closer – 5.7 to 5.2. How much can we trust the defensive numbers? Not much for a single season, they are more reasonable for multiyear or careers. 1991 defensive ratings are based on project scoresheet data, which simply was not anywhere near as consistent or reliable as the data we track today, especially since Statcast.
We can trust that both players were good defenders. Bonds was a gold glover, Pendleton didn’t win one that year but had 3 for his career (including the following year). It’s close enough that I can’t be too upset over either one of them winning, and Pendleton was a great story as the best player on a team that shocked the world by going worst to first.
If the Adidas Pride sneaker has too little LGBT essence, this Converse high-top may contain too much — that is, unless you absolutely love rainbows.
Keith
Your sarcasm toward Larry Bowa on page 72 Shows how little you know about Bowa. Lumping him with Drew was ridiculous. Sarcastically calling Bowa a baseball luminary showed a lack of class on your part.Having seen most of Bowa’s games with Phils I can assure you he was a great fielder. He was sure handed with great range and a great arm. You should learn something about Bowa. It’s obvious you know very little about him.