Laying the Foundation Episode IV: Resources

Starting with Episode IV… get it? I said GET IT?!?!

At this early juncture, it is difficult to know exactly to whom this blog will appeal. I suspect some people will already be familiar with metrics such as Wins Above Replacement (both the fWAR and rWAR varieties), OPS (On-base Plus Slugging%), OPS+ (On-base Plus Slugging% normalized to league average). Others will barely have heard of more mainstream metrics such as AVG (batting average) and RBI (runs batted in). I suppose this blog will ultimately try to strike a balance between the two audiences – at least for a time (hopefully some will decide to come along for the ride). In an effort to get people up to speed before the blog really takes off, I have decided to dedicate a few posts to introducing some of the resources and metrics that I find useful (and, hopefully, adequately explain why I find them useful in a way that will not bore you to tears). Some of you are whole-heartedly invited to skip these posts if you find them elementary, and some of you may decide that this is the stop on the route at which you disembark.

(You will find that I use parentheses… a LOT)

Let’s talk about stats, ba-BY! (click at your own peril)

I have to admit I am basically a neophyte user of both of these sites. Oh sure, I’ve been using them both for years, but my relationship with them is not unlike the one most people have with Excel – many of use a few basic functions, but (to paraphrase one of my best friends) most never even scratch the surface this absurdly powerful program’s capabilities. No introductory description will do either site justice (at least, no introductory description of which I am capable). If you are so inclined, I invite you to visit both sites and start messing around (a fun starting place is to search for one of your all-time favorite players and see what you find that you already understand and what you can teach yourself through deduction). If you have specific questions, the sites have explanations of most metrics, google can answer many a query, and I’d be happy to try to answer questions as well (however, save yourself the trouble of asking me where babies come from – I think the above link probably told you all you will EVER need to know).

You’ve been so good if you’ve made it this far! It’s probably time to reward you with a picture of a small animal.


Baseball Reference is basically the ultimate online baseball card collection – one can find detailed statistics (both accessible and incredibly specific) for near every player that has ever played professional baseball. It even has records for minor league players, Japanese league players, and historical leagues such as the Negro Leagues (don’t jump down my throat – that is how they were and are still referred to). Baseball Reference does keep track of stats up to the morning that of access and employs many in-house metrics and formulae and is valuable for comparing specific scenarios or isolating similar calibers of seasons put up by players spanning the professional game’s history using its Play Index tool.

Fangraphs is a similarly massive site. It has its own house-metrics that are often similar in principal to some those used on Baseball Reference, but using its own proprietary formulae. It also employs projection tools from a variety of sources that attempt to prognosticate future performance based on both existing data specific to the players in question and extrapolation of longer-term statistical trends. For example, a player in his age-30 that puts up a good season with the aid of some batted ball luck will likely be projected to perform a little worse in his age-31 season year based on his age and the inescapable statistical force of regression (batted ball luck tends to balance itself out over time). The beefiest of Fangraphs’s stats can only go back to the early-to-mid 2000s, but it nonetheless sports an impressive volume of statistical data throughout the compass of MLB history. Fangraphs also boasts many contributing writers who explore a wide range of topics (well, a wide range within the category of “statistical topics”). Quite honestly, I am tempted every day to simply make Fangraphs my startup page, but I fear that would confirm many a suspicion that I am some kind of freak.

In the interest of full-disclosure, I will state now that most of the stats I will pull out of my ass employ in this blog will come courtesy of Fangraphs. The next post will explore some of my favorite metrics in greater detail.

Just remember: you were much happier not knowing.


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