[This post was started a few weeks ago when the Hall of Fame debates were raging. I never got a chance to finish the post to my satisfaction, but since I already put a lot of time into it, I figure that I'll publish what I have anyway. Hope you all enjoy.]
Over the last few years, the term "sabermetrics" and the concepts related to it have started to seep into the mainstream baseball consciousness. The now-famous book, Moneyball, is what truly ignited interest in the media and among the common fan, and now, years later there are varying degrees of awareness, comprehension, and acceptance of these ideas.
On the one side are the sabermetric experts, the men and women who pioneered the research providing the foundation of sabermetrics, as well as forward-thinking blogs and those who now might be employed in baseball to do this kind of statistical analysis. On the complete opposite end of the spectrum are "average joe" types of fans who have never heard of "sabermetrics" as well as those who have and have decided that they don't provide any positive value to the game. At this point, most writers, even mainstream writers, have at this point at the very least acknowledged the existence of sabermetrics, and many have written primers on the topic or go so far as to use them themselves.
The group that you seem to hear from the least, ironically, are those in the middle - people who would take sabermetrics and use them as a rational compliment to everything they already know about baseball. Most discussion of sabermetrics, as a field in general, has been very dogmatic. Much like politics here in America, most of the discussion is dominated by extremes. So, why all this by way of introduction?
Last week, I posted a lengthy (probably too lengthy)
write-up of Dillon Gee and explained why I think the mainstream expectations of Gee resulting from his successful major league cameo were too high. I looked at some minor league numbers, his pitches and velocity, and some comparable players, and tried to temper everyone's expectations a little bit. As I am lucky enough to have traffic to this blog, and a lot of interesting, critical, insightful readers, I got some feedback on the article which disagreed with me. That's great -- in fact, the rapid exchange of ideas and viewpoints is exactly what makes blogs the incredible medium that they are.
In this case, however, the person who responded went by the handle "AgainstSabermetrics" said something which I felt compelled to address:
How many would love to be good enough to beat the Phillies starting on the bump? Why do you sabermetric guys all cover each other's backs? The results will come. The Mets minor league blog said that if Gee got to start in the Show, it probably would not go well. That statement was all based on sabermetrics. As the previous responder showed very well, the percentages(numbers) don't always add up. The results are real. It will be interesting to see how scientifically viable the sabermetrics are with this player. Even more interesting, how will the sabermetric scouts respond to the results that defy their science?
Like I said, it's cool if you want to disagree with the conclusions I've drawn. However, I see a few things in Dillon Gee that make me think he'll have a harder time than most in transitioning to the major leagues -- maybe you don't. The part of the response that I excerpted above, however, is a common attitude and one which I think is silly.
There's no reason to be "against" advanced statistics, sabermetrics, or its derivatives, for exactly the same reason why a person who is into advanced stats shouldn't be "against" batting average, or scouting, or RBIs. They exist - regardless of our personal opinions - and it is simply up to us to decide for ourselves how important we think they are.It's unnecessary to make it a binary "for" or "against" sabermetrics argument. It is a false dichotomy. As a matter of fact, in this case, I didn't simply use sabermetric stats to make my decision. If you click through to the article, I look at ERA, strikeouts, reports of his pitches and their velocity, and comparisons to pitchers who I considered to be similar major leaguers. Here is my conclusion in a nutshell:
In summary, there are three things that Petit, Bannister, and Gee have in common that make me wary about Gee's ability to strive in the majors.
1. Low-minors success based on excellent K/BB ratios
2. Right-handers with low-velocity fastballs (topping out around 89)
3. Escalating HR/9 ratios, particularly in Triple-A
When you throw soft, and depend on location, it is a very bad if not fatal sign when more advanced hitters can start taking you yard with regularity.
These are not advanced sabermetric concepts -- and in fact, I try to keep away from FIP, WAR and similarly advanced statistics in my writing to keep it accessible. I'd like for my Dad to be only somewhat confused at what I'm talking about as opposed to completely lost.
But back to the original point: the battle between scouts, and statistics, and advanced statistics is really a silly one. Each of those angles provide you with a different kind of insight, and they should all be considered. All of them reveal something, and all of them, I don't care which one you like, will sometimes mislead you. It is up to you - the reader, the writer, the fan - to try and give each its appropriate weight.
I've heard a lot of people - from big-time writers down to bloggers and commenters - say that they "reject" sabermetrics. One obvious example of a writer who has rejected the idea of advanced statistics is Murray Chass, who used to write for the New York Times. Murray went so far as to
say silly things like this:
I suppose that if stats mongers want to sit at their computers and play with these things all day long, that’s their prerogative. But their attempt to introduce these new-age statistics into the game threatens to undermine most fans’ enjoyment of baseball and the human factor therein.
People play baseball. Numbers don’t.
Ouch. He later on called those who enjoy sabermetrics "devotees" of the concept and "followers" of those who have studied it. Creepy, huh? If you're going to bash sabermetrics, you should eat least do it in a way that's funny, like
Jon Heyman did when he called those who follow those numbers
VORPies:
Sorry VORPies, Rollins was the right choice... I wasn't shocked that stats people have taken issue with Rollins winning the MVP award. There are numbers crunchers out there [] who believe baseball writers rank somewhere between morons and idiots for voting Rollins as MVP over David Wright, who had a higher VORP. The stat people seem to believe VORP [] defines a player...
It gets a little crazy down there in the trenches, I guess, and people always act scared when they are confronted with something that they don't understand. Even in a children's game like baseball. But there's no reason why a professional writer, broadcaster, or scout, can't make a slight effort to learn a thing of two about the advanced stats and what they have to say and enlighten their own point of view. A great, great example of this is what Bill Simmons did
a few short months ago:
See, I stopped writing about baseball these past two years when the sabermetrics movement became too complicated for my liking... I just hated the finality of it, the concept that numbers could trump anything I was watching with my own two eyes. If numbers always prevailed, what was the point of watching baseball or having arguments about it?
Thirty-five years later, those numbers don't tell us nearly enough... Throw everything together (visual and sabermetric), and 1975 Freddie Lynn stands the test of time. But I had to do some work to prove it. And that's what this is all about: work. Not everyone wants to work to follow sports. This isn't school. We don't want to do homework. We don't want to study. We just want to watch games.
I spent March reading and surfing sabermetrics for mostly selfish reasons ("I want this column to be better," "I want an edge for fantasy purposes," "I'm bored"), but also because the advanced formulas weren't nearly as intimidating as I had expected. Full disclosure: I, um ... I-I kinda like them. I even understand why stat junkies take it so personally whenever a mainstream guy spouts out an uninformed baseball opinion. It's too easy to be informed these days. Takes a lot less time than you might think....These stats make understanding baseball more fun. At least for me.
And they make them more fun for me as well. I love baseball, and one of the most interesting and unique things about it is that it is a sport in which everything can be measured. There are statistics for the National League on baseball-reference.com dating as
far back as 1876! Yes, you read that right. There are statistics for the National Association which go back even further - there are stats and standings
from 1871. Do you want to know how many hits Harry Wright had in 1871? Well, you can find out by clicking
here. He was born in 1835.
The point is, baseball is a beautiful game which can be summed up by statistics in a way that no other sport can. In football, every play is affected by dozens of people. In basketball, there are ten men on the court at any moment and the numbers you derive from that are affected by those around you, the offensive scheme you're running, etc. But in baseball, it's just you. The batter and pitcher face off in a miniature play we've seen a million times. So when you look at that Harry Wright player card, you're not just going to see hits. You're going to see walks. And strikeouts and stolen bases and grounded into double plays. By the time 1894 rolled around, they had started counting sacrifice hits. For pitchers, they were already keeping track of complete games, home runs allowed, wild pitches, and balks. None of those are essential to the enjoyment of the game - but all of them were tracked shortly after the American Civil War, and before the telephone, and before electricity, and before homes had running water.
Sabermetrics are an interesting tool. And for me, I like them because they allow me - if I am willing to do the work - to look at a player who I may not have had the opportunity to see play very much on television and help me develop an informed opinion of them. I don't consider them to be the be-all-end-all of player evaluation. I believe that most of the intelligent folk who follow advanced statistics feel the same way.
One of the major criticisms you hear from those who dislike sabermetrics is the idea that someone can look at WAR, or wOBA, or some other number and immediately decide that one player is better than another because of it. That's not what it's all about. It's simply a way that we can take the information that we have and put it into perspective - across leagues, across generations. When you think about it, even batting average is a derivative stat: H/AB = BA. Is that much more outlandish than OBP? Or SLG? Or OPS, which is simply OBP+SLG?
As for the reader who commented and disagreed - thank you for putting my idea on trial. In doing so, one would hope that we can come to better, more accurate, and more useful answers. For instance, if anyone clicks through to the article and reads the comment in its entirety they can see it themselves, the commenter mentioned that Gee could touch 95 with his fastball but was operating around 88 in an effort to work the corners of the plate. I thought that the excerpt from the behavioral doctor was interesting as well.
Being for or against sabermetrics is a silly concept. Mainstream writers who poke fun at saber-style writers and articles should be ashamed of themselves. Sabermetricians have done some truly incredible and interesting research over the years, and reading it has greatly expanded my appreciation of the game. The statistics available to me on Dillon Gee and of players who I thought were similar based on actually watching him, allowed me to form a more well-educated decision than if I had simply watched him pitch four games in September.
If you're trying to make an informed decision, you should take all the information available to you and decide yourself what you think is the most important.
