At the end of Saturday’s installment of Toolbox, I promised to move ahead to the pitchers this week. Once again, good feedback and a general desire to make sure the class is all on board with what we’re talking about before moving on to the next thing keeps us from going forward. That’s mainly my fault—the last few Toolboxes have been light on the Further Reading and bullet point sections, which might have helped clarify issues before they got out of hand.

We’ll let reader S.T. lead things off:

Is Cameron Maybin playing in a park that suppressed home runs by half or so? He has hit 12 this year and your column credits him with 22. That seems like a very generous translation—or a data-entry error.

There’s no data-entry error, there. The problem is that the list I posted at the end of my column was a “peak” translation, which as I explained, is probably more appropriately termed a projection than a translation. Let’s use Maybin as an example of how the three reports contained in the Minor League Statistics & Translations (MLST) page work:

Player            AB  HR  BB   SO  SB  CS  AVG  OBP  SLG   EqA EqR  BABIP  POW  Krt
Cameron Maybin   318  12  46  101  17  6  .264 .359 .453  .280  51  .351   276 .277
Player A         336   5  60   61   3  8  .283 .406 .390  .280  53  .333   131 .154
Player B         451   7  24   67  27  7  .333 .365 .435  .280  67  .379   120 .141

First, to the left we have the Real Stats section. Real stats are pretty self-explanatory—if a guy has 90 hits in 300 at-bats, he has a .300 batting average, with no accounting for ballpark or league difficulty or anything else. I’ve stacked up Maybin’s season at Double-A with two other players who are also posting the same EqA—untranslated, based on the real stats—in the Southern League. For right now, those two players will remain anonymous. Please note that Player B doesn’t walk, and Player A, with his high walk rate and complete lack of speed, is someone that many people who don’t know anything about us other than what they read in reviews of Moneyball, would erroneously consider a “Baseball Prospectus-type player.”

Player            AB  HR  BB  SO  SB  CS    BA  OBP  SLG   EqA EqR  BABIP POW   Krt
Cameron Maybin   329  13  38  99  11   4  .240 .319 .416  .256  43  .304  248  .270
Player A         354   6  48  69   2   5  .234 .334 .336  .239  39  .276  126  .172
Player B         461   8  20  71  18   5  .291 .318 .390  .251  54  .330  118  .148

Now we’re looking at the translated numbers for Maybin and his peers. As you can see, his season doesn’t translate to hitting 22 homers in the bigs, but the league apparently suppresses power enough that, at the major league level, it’s expected that Maybin (and each of his anonymous compatriots) would have right around the same number of homers he has in the minors. Even though their real stats had them all at the same EqA, notice that they diverge when we do the translation. Player B stays pretty close to Maybin with an EqA in the .250s—below-average major league production, but not bad for someone two levels away from the majors; Player A lags behind the others, despite having a better translated OBP.

Player           Pos  Age    AB HR  BB  SO  SB  CS   BA  OBP  SLG   EqA  EqR
Cameron Maybin    CF   21   329 22  53  83  15   6 .283 .382 .553  .310  66
Tonys Gutierrez   1B   24   354  6  49  68   2   5 .237 .338 .342  .241  40
Alcides Escobar   SS   21   461  9  29  59  21   6 .306 .344 .414  .269  63

Now we’re going to add a little more data into the mix. Now you can see that Player A was Tonys Gutierrez, a 24-year-old first baseman in the Reds organization, and Player B was Alcides Escobar, a 21-year-old shortstop that Kevin Goldstein ranked as the sixth-best prospect in the Brewers system. The peak translation gives us a glimpse of what the player might be like at the top of his game—usually at or around the age of 27—based on his statistics and typical aging patterns. Gutierrez’s peak translation is basically the same as his regular translation—no speed and no power, plus being old for the Southern League, mean that there’s no room for growth in his game. Escobar turns out to be a decent major league bat at his peak—if he’s going to make an impact in The Show, it’s his speed and slick middle-infield glove that’s going to get him there. Meanwhile, Maybin’s superior combination of power, speed, and youth (like Escobar, he’s 21) lifts him head and shoulders above these peers in terms of peak value. That’s the difference between a great prospect, a decent prospect, and a non-prospect.

You’ll notice that there are a few numbers that are currently included at the end of the hitters’ stat reports which don’t seem to be part of the standard package, and which appeared in the first article (but not this one). Reader T.P. takes issue:

I was reading your article regarding the Minor League Statistics Translations, and it looks wonderful, I just wish I understood all the categories. Is this something you have to buy your book BP 2008 to really understand? I mean when I did a glossary search things like ABIP, POW, Krt got zero results. As did SA, which I think is slugging average (but how exactly that is more meaningful than SLG% I have no idea or OBA vs OBP). Have you ever thought about having a header or footer with a statistics glossary on the actual report? And one final question what do the numbers represent on the far right? After what I assume are AB’s at a secondary position. Do you perhaps have a primer somewhere that I look at as I look at the report?

It’s funny, I have a fricking college degree, I’ve been going to baseball games since I was six, my sister babysat for Sal Bando… (okay the babysitting thing probably isn’t relevant to much, except showing what a super-duper fan I am:) and yet sometimes I look at the reports at BP and feel sooooo stoooopid. But I want to understand, so maybe for the babies to sabermetrics out there, what is the best way to get a handle on something like the Minor League Statistics and Translations report?

First of all, don’t feel stupid; that’s not what we’re here to do. I gave you data without properly noting what it is or telling you where you could find it, so that’s on me (and on us, not on you). You’re right that SA stands for slugging average, a term that’s occasionally used interchangeably with slugging percentage (SLG), just as on-base percentage (OBP) and on-base average (OBA) are used interchangeably by a very few people. What you were looking for as “ABIP” was BABIP (batting average on balls in play) which, I assure you, is in the glossary section. Indeed, you should see the definition pop up when you roll your cursor over the acronym. [Editor’s Note: We look forward to the eradication of these sorts of idiosyncratic variations on common usage in the very near future; hence the corrections in the tables in today’s column.]

There are, however, two metrics that were bound to cause some confusion: “Krt” from the original article is an abbreviation for K Rate, which itself is synonymous with strikeout rate (or SO Rate). Strikeout rate is just strikeouts divided by plate appearances, and it’s one of the factors that are used to determine a hitter’s peak potential. The other stat, POW, is relatively unheard of: it measures Power on Contact. Basically, it’s Isolated Power, with strikeouts taken out of the equation. These terms will be added to the Glossary shortly. Remember, if you find any other problems with the Glossary, or things that are missing, rather than feeling stupid, feel free to drop me a line using the link to contact me at the bottom of the article, just like T.P. did.

Brad Oakchunas was also suffering from a lack of information:

Would it be too much to ask that the players just be listed alphabetically? Most people would search for individuals and it is very difficult to do that this way, especially if you don’t know what city he played in. Just now, I was looking for Dallas Braden. I actually do know that he played in Sacramento, except I can’t even find Sacramento (What can possibly be the abbreviation if not SAC?) on the list and even if I could I’d have to scroll down until I happened to get to the player that matched his PERA. Very complicated! Thanks for any help you can give.

If you know what league the player you’re looking for is playing in, there’s a simpler way of locating him, even without us alphabetizing the report: you can use your browser’s search function (this can be found under the “Edit” menu, as “Find” or “Find in This Page”) to pull up the player’s name. However, you have a very valid point about the team name abbreviations. For those of you with a copy of Baseball Prospectus 2008 handy, you can flip to the back of the book to the section called “Team Name Key and Park Factors” to confirm that Sacramento is, indeed, SAC. However, since some of you may be browsing the site from somewhere where your copy of the annual isn’t handy, or may (gasp!) not actually own a copy of the annual, we’ve put up a handy page with a key to all the abbreviations for the leagues listed in the MLST.

So, just to be clear, let’s bring back the bullet points and sum things up:

Advantages of the MLST Report:

  • The Real Stats section gives unadjusted stats, including several of our advanced stats, updated regularly, for all the full-season minor leagues.
  • The Regular Translation section puts all those leagues on the same footing, allowing for apples-to-apples comparisons between major and minor league performances at various levels.
  • The Peak Translation section provides projections of each player’s performance, which gives us a better idea of a minor league player’s standing as a prospect.

Limitations of the MLST report:

  • It’s not sortable. Although the report helpfully provides certain leader boards, such as the highest EqA and EqR in each league for each category (Real/Regular/Peak) there is other analysis, such as combining leagues or establishing the performance of a player who’s gone through multiple levels, that takes some work. Although the numbers are easy to find, it is hard to process them into anything other than the pre-made reports. For example, if someone wants to compare minor league catchers, they’d better be prepared to do a bunch of cutting and pasting into Excel.
  • Slight incompatibility with the Equivalent Average report. The two reports draw from slightly different sets of data, so you’re likely to see small differences in the way that major league EqAs and EqR are computed between the two.
  • Doesn’t include other BP stats. Having this report really whets my appetite for minor league VORP, Support-Neutral stats for starting pitchers, and Win- and Run-expectation-based reliever stats. But that’s just getting greedy.

Further Reading

Clay Davenport, “Is There Such a Thing as a Quadruple-A Player?” in Baseball Between the Numbers (Basic Books, 2006). This chapter explains the basics of translated statistics as they relate to minor league performance.

Clay Davenport, “Making Changes: A New Look at Minor League EqA.” This 2004 article goes into greater detail on the basis for peak projections (here called Future DTs).

Clay Davenport, “Baseball Prospectus Basics: About EqA.” Explains the basic math behind EqA, and compares it to other, similar advanced stats. It is worth noting that while many people conflate EqA and the Davenport Translations, they are actually separate concepts—as we see in the Real Stats Minor League report, EqA functions just as well outside of the translation framework.

To learn more about the prospects mentioned in the last two editions of Toolbox, you can refer to Kevin Goldstein‘s Top 11 lists for:
Colorado (Dexter Fowler)
Milwaukee (Mat Gamel and Escobar)
San Diego (Kyle Blanks)
New York Yankees (Austin Jackson)
Florida (Maybin)
Pittsburgh (Andrew McCutchen and Neil Walker)
Toronto (Travis Snider).