Baseball Knowledge 101 - Introduction and Syllabus

Believe me, we could keep producing snarky comments about beat writers and Astros management for a long time -- late Septemeberish to be exact. Instead, we’ve decided we’d like to do something a little more productive. Something that, hopefully, will make your readership of this humble little blog all the more enjoyable.

Evan and I first were introduced sabermetrics and different ways of viewing the game like a lot of people our age: Moneyball. However, for us, Moneyball merely whet our appetite for “baseball knowledge” as it only talked about the sabermetric concepts employed by the A’s in their quest to succeed on a small budget. For myself, I consider that book to be life changing -- which I know is extremely sad, but what it did for me was take me from casual observer of the game of baseball to someone who appreciated the art form of winning baseball on an entirely different level. The nuances of which I’ve come to find so fascinating I had to blog about it.

While it allowed to us to think about the game differently, we still struggled to grasp how to think beyond those basic concepts or truly employ them in our observation of the game. This quest for deeper understanding lead us to the internet. We soon discovered sites like The Hardball Times, Baseball Prospectus, and Tom Tango’s personal site. We then found ourselves right in the thick of where a great deal of sabermetric thinking was formulated and expounded upon for the last decade plus. In an effort to better understand some of the complicated mathematical and often economic analysis, I even took a few college courses specifically to enhance my ability to employ sabermetric analysis. Again, sad. Once school was out last year, I picked up a copy of Baseball Prospectus’ Baseball Between the Numbers: Why Everything You Know About the Game is Wrong. I’ll be the first to admit that in parts, it was like reading a college text book, but overall, it was easily accessible, well paced, and it completely changed how I thought about the game. Evan, to whom I’d report to on the brilliant and insightful ways to think about baseball from the book, eventually picked up his own copy.

The rest of the summer was spent emailing articles we found archived on sites back and forth and trying to play catch-up on the bounty of baseball knowledge available to us. While we had briefly tried our hand blogging during our baby steps in baseball analysis, we pretty much put it on hold as we dug deeper into the wealth of knowledge sabermetrics provided us. During the waning months of the season, the post season, and the entire off season pretty much the only dialogue between us was applying our new found baseball knowledge to the game and the wheelings and dealings between teams during the off-season.

After pestering another Astros blogger for sometime with our pious indictments of this opinion or that (which have since proved dutifully flawed because of our subjective bias, more on that at th end), we eventually picked up the blogging torch again in attempt inspire Astros fans to think about their hometown heroes in a different, more objective light. We’ve found a lot of the responses to the stat laden posts to be rather tepid and we fear it might because we’ve gotten ahead of ourselves. In an effort enhance the insight with which we are trying to provide you, our reader, we are going to try a weekly(ish) serious of installments walking you through the same inquiries we made into baseball and the knowledge they yielded. You should think of them as essay’s almost, as we’ll provide all the research and attempt to summarize and analyze them for you. Our hope is that we can open up the slowly growing readership we have developed to the ways that we have come think about the game of baseball.

To start, it’s probably necessary to briefly define sabermetrics and explain what it aims to do. The best definition I found with a quick Google search came from Wikipedia:

"Sabermetrics is the analysis of baseball through objective evidence, especially baseball statistics. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research. It was coined by Bill James, who was among its first proponents and has long been its most prominent and public advocate.

From David Grabiner's Sabermetric Manifesto:

Bill James defined sabermetrics as "the search for objective knowledge about baseball." Thus, sabermetrics attempts to answer objective questions about baseball, such as "which player on the Red Sox contributed the most to the team's offense?" or "How many home runs will Ken Griffey, Jr. hit next year?" It cannot deal with the subjective judgments which are also important to the game, such as "Who is your favorite player?"[1]

It may, however, attempt to settle questions such as "Was Willie Mays faster than Mickey Mantle?" by establishing several possible parameters for examining speed in objective studies (how many triples each man hit, how many bases each man stole, how many times was he caught stealing) and then reaching a tentative conclusion on the basis of these individual studies.

That gets us close to what I have come to regard what sabermetrics does. Its benefit, in my mind, is its ability to answer objective questions by providing the inquirer with facts. It allows you to say whether or not a team should search out someone with a good batting average vs. someone with a average batting average, but superior on-base percentage because you can test the correlation to run production between the two. It allows for analysts to test strategies in baseball by determining the cost/benefit of different strategies (like sac bunts, stolen bases, IBB, etc.) in different game states. It can’t provide definitive answers, but it can help point you to the “truest” answer because it objectively provides the facts. Like all objective inquiries and the test surrounding them, sabermetrics, at most, provides support for a hypothesis, not concrete answers. Akin to a peer-reviewed journal, there is a lot of testing of findings and from those tests, the nuances of the truth are uncovered.

As we paint the picture of what we have come to understand about how to better analyze baseball, we encourage you to get hands on with the sources we cite. Over the last 18 months, Evan and I have read a lot of argument, counter argument in formulating our knowledge and we hope to boil that process down for you. However, we don’t want to be thought as presenting the truth about subject X or subject Y. These articles are to serve as a guide to getting your feet wet in the sabermetric world, not a cliff notes for baseball knowledge. We hope you’ll enjoy our offering of the next few weeks and further more we hope that you’ll engage in the information.

In the end, we hope that if we can open up or readership to the concepts we so love to employ in baseball analysis so that we can all keep each other honest. As I stated earlier sabermetrics provides objective answers to objective questions, however if one subjects the objectivity to biases, then often times you weaken the tool. I myself am guilty as charged. On May 13th I looked deeper into the Astros stats to see if their lightening hot streak was legitimate or not. Because I so desperately wanted the answer to be yes, I did a poor job of interpreting the numbers. The best face saving I could bring myself to do came on May 27th, and even then I couldn’t bring myself to say that the numbers indicated that our streak was based on luck and that the numbers pointed to a crash burn. In the end, we hope that this exercise will force us to be more honest with ourselves before we report on the Astros, or enable you to call us on any BSing we try to put forth.

Look for us to alternate between pitching and hitting before we jump to fielding, but here is a tenative syllabus of what we hope to accomplish:

Pitching Stats
-W, ERA, and Rate Stats
-DIPS, LIPS, FIP
-Relievers
-Pitch/fx and the next frontier

Hitting Stats
-BA, RBI, R, OBP, OPS
-BaseRuns, RC, etc.
-Line-ups and Protection
-Batter/Pitcher match-ups and other splits

Fielding Metrics
-Fielding percentage, and the rest

Putting it Together

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