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What Is Sabermetrics? And Which Teams Use It?

Posted By Bradley Woodrum On February 9, 2012 @ 11:00 am In Angels,Astros,Athletics,Blue Jays,Braves,Brewers,Cardinals,Cubs,Diamondbacks,Dodgers,Giants,Indians,Mariners,Marlins,Mets,Nationals,Orioles,Padres,Phillies,Pirates,Rangers,Rays,Red Sox,Reds,Rockies,Royals,Tigers,Today in FanGraphs,Twins,White Sox,Yankees | 69 Comments

It is a simple question.

What is sabermetrics?

Not the history of it, but what is it, right now? What is, in our nerdiest of lingoes, its derivative? Where is it pointing? What does it do?

Last Tuesday I created no little stir when I listed the 2012 saber teams, delineating them according to their perceived embrace of modern sabermetrics.

Today, I recognize I needed to take a step back and first define sabermetrics, because it became obvious quickly I did not have the same definition at heart as some of the readers and protesters who gathered outside my apartment.

I believe, and this is my belief — as researcher and a linguist — that sabermetrics is not statistics. The term itself has come to — or needs to — describe more than just on-base percentage, weighted runs created plus, fielding independent pitching, and wins above replacement.

Sabermetrics is the advanced study of baseball, not the burying of one’s head in numbers.

Personally, I see sabermetrics as breaking down into three separate, equally important distinctions, and one massively important, yet fully amorphous unknown element. Again, fastening on our mathematics overalls, we would describe this as:

f(Sabermetrics) = statistics + scouting + business + ε

In words: Sabermetrics the study of baseball statistics, baseball scouting, baseball business, and anything yet-known or missed by myself (which is the “ε” epsilon).

More specifically:

Scouting is the more subjective study of baseball. All study is somewhat subjective — if it was not, then economists and statisticians would always agree, yet they most certainly do not.

Scouting analyzes the physical attributes and the medical attributes of a player — is he a big-bodied slugger (the type that fades early in the MLB)? does his pitching motion preclude potential elbow injuries or is he a problem waiting to happen? should he have an more open stance? is he tipping pitches? is he stepping early to first base? These are the questions scouting and only scouting can answer.

For amateur players, international free agents, and even guys working through the minors, scouting must be a major component — if not the major component of any analysis concerning them. Not only are these players likely years away from the MLB — and thereby likely to change physically and run the risk of injury — but they are also coming from leagues and schools where the available statistics and league environments produce numbers that are relatively unreliable. There is no UZR, no FSR, no Pitch F/x, no Home Run Tracker.

And at the major league level, scouting can find a problem faster than statistics can. The stats are subject to random fluctuation, but if a pitcher starts falling off the mound in a different way, a scout (or pitching coach in this case) can identify and correct the problem before the statistics — or the team’s record — can even notice.

Scouting can also provide valuable insight into a player’s mental or non-physical attributes. The statistical profile of John Outfielder may say he’s a free-agent catch:

Career: 970 PAs, 31 HRs, 18 SB, 102 wRC+, 26 years old.

But the mental scouting says: Elijah Dukes.

Dukes may be the hyperbole of a player profile in mental shambles, but the need for mental analysis remains. Teams can head off major problems well in advance if they can early on recognize destructive or dangerous patterns in a player’s lifestyle.

Statistics, in my humblest of opinions, breaks down generally — very generally — into three areas league-wide, player-specific, and game strategy avenues of research. These three distinctions, of course, overlap so much as to nearly claim they are all one. And that is fine.

The important note here is that statistics was long-neglected. Branch Rickey and F.C. Lane were about the only two true sabermetricians from baseball’s beginning to modernity because they understood that the contemporary branch of statistics was sorely under-utilized and sorely out of date.

So, in the early 2000s, with the help of the Internet and Michael Lewis’s Moneyball, the world of baseball statistics boomed into a full-fledged fan obsession. Of course, Moneyball, both the book and the movie, helped create a dangerous pendulum swing — the arena of baseball study shifted so heavily into the realm of statistics that scouting began to garner a negative connotation — which is not good.

Lastly, we have the business aspects baseball study. Sadly, because our information is limited, we cannot dive as fully into this field. We may have attendance numbers, ticket prices, contract payouts, and general economic data, but we still lack a vast amount of information and must reverse-engineer answers to our most pressing questions — say, how much does Albert Pujols or Ichiro Suzuki actually bring in annually outside of their on-field production? We do not know for certain, but we can guess.

For clarity’s sake, I see the business branch breaking down into at least four subsets: contracts (which we have almost full information on and have made great strides in understanding), media deals (of which we know very little — only the briefest of press releases give us information on this matter, to my knowledge), stadiums (which include a whole bucket of issues ranging from national to local), and economics (or how the game relates to, is affected by, and affects the national and international economy).

Are these distinctions I am making somewhat arbitrary and not entirely universal? Yes. Hell yes. I have done my best to analyze the general wings of baseball, but I fully recognize this is just one man’s logic. As more voices offer feedback and more fields are uncovered, the breakdown should grow and shift and be thrown out entirely and resurrected later. At current, though, this breakdown makes sense to me.

To neglect any one of these three known branches (as well as the pursuit of the unknown) is to be an incomplete and sub-optimal organizations. It is not to be a losing team, mind you. It is my understanding the Philadelphia Phillies are very much a scouting-heavy and statistics-light organization, yet they have been wildly successful. Likewise, the Seattle Mariners and Cleveland Indians are widely considered fully sabermetric teams, but they have failed to reach a level of sustained success like the Phillies.

In the saber team lists, I used the terms Highly Analytical Organizations, In Between Organizations, and Old School. I confessed in the comments how I longed for better terminology — because I imagine all MLB teams are highly analytical, even if they employ zero statisticians.

So, let us use this three-branch break down to redefine our list of 2012 sabermetric teams. If we look at the teams once again, and analyze where their analytical leverage seems to come from, whether it is coming from just business and scouting or all three branches, we get this:

Alphabetical by mascot. And remember, this is as of 2012.


3 Branch Organizations

Oakland Athletics
Houston Astros
Toronto Blue Jays
Chicago Cubs
Arizona Diamondbacks
Cleveland Indians
Seattle Mariners
San Diego Padres
Pittsburgh Pirates
Texas Rangers*
Tampa Bay Rays
Boston Red Sox
New York Yankees


2-to-3 Branch Organizations

Milwaukee Brewers
St. Louis Cardinals*
New York Mets**
Philadelphia Phillies
Chicago White Sox


2 Branch Organizations

Los Angeles Angels
Atlanta Braves*
San Francisco Giants
Miami Marlins
Washington Nationals
Baltimore Orioles
Cincinnati Reds
Colorado Rockies
Kansas City Royals
Detroit Tigers
Minnesota Twins


1 Branch Organizations

Los Angeles Dodgers**

*I’m especially unsure about these teams.

**Given the Dodgers’ and Mets’ financial problems,
they are the only two teams who appear to be without
analytical leverage from the business branch.
This may have changed recently.

I would like to reiterate (from the last piece) that these are merely my perceptions (coupled with community suggestions). If you work or worked for one of these teams and I have gotten the team’s placement wrong, please feel free to alert me to the oversight. Naturally, I weigh insider’s perspectives more heavily.


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