Projecting Gaby Sanchez, Pt. 1: Major League Equivalents

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Lately, I’ve been seeing quite a few people desperate to see Gaby Sanchez and what he can do. This should come as no surprise, since the Marlins currently have a scrub playing third base in Emilio Bonifacio and Marlins fans have heard enough of Sanchez to wonder whether the grass is greener on the other side. It should be, given that the grass on this side is stomped on and browned from months of poor lawn management (I’m looking at you, Fredi Gonzalez, Larry Beinfest, and Michael Hill). But how much more can we expect from Gaby Sanchez that we aren’t getting from Emilio Bonifacio?

Well, nny has posted over at FishStripes and at Fish Guts (try the site out, tell me how you like it!) his projections for a variety of Marlins prospects. Here is the one for Cameron Maybin and here’s the joint one for Logan Morrison and Gaby Sanchez. They are definitely worth a read if you’re interested in speculating on the future, as we all are as Marlins fans used to anxiously anticipating when the future stars of current trades will pan out and become what we’ve been sold they would be. His projections are based somewhat on a solid principle, that while a hitter’s ability to produce hits isn’t entirely in his control and will vary with the level of competition, more peripheral values like swing rate, contact rate, and strikeout and walk rates will tend to stabilize faster and be more indicative of future performance. As you might have seen in my previous projection project (I love alliteration) of Chris Coghlan, I like this process and want to use it to determine a player’s potential future.

But unlike the process I used with Coghlan, where I took the data we’ve seen so far in his rookie season and looked at potential comparables in the majors right now (and came up with a pretty good comp in Chone Figgins, the name I had in my head all along), we’re going to start with a different approach with Gaby Sanchez. While Sanchez has barely played at all in the majors, he’s played over three seasons in the minor leagues. With those seasons come almost 2000 plate appearances worth of batting data with which to work.

Unfortunately, such data is relative to minor league competition, so how useful can it possibly be? Well, using MinorLeagueSplits’ Minor League Equivalency Calculator, we can translate that data into major league equivalents, or MLE’s. You can check out its basis over there, but I’ll tell you that minor league park factors are based on Dan Symborski’s factors (not totally up-to-date as he released a 2008 version and I’m not sure if the site updated the factors since 2007, though based on the updated minor league numbers that they have, I’m guessing they did update) and the league factors were provided by the ever-popular Sean “CHONE” Smith. Read his stuff, because he’s the man.

So, what did I do with this calculator thing? Let’s take a look. First I started by converting all of Gaby’s minor league numbers to major league equivalents. Of course, take the 2006 and 2008 numbers with a small grain of salt, as I’m unsure of the calculator’s park factors for those seasons (I’m almost certain the low-level values will be off by a bit, the 2008 numbers I’m a little more certain about). Here are those numbers in pretty Excel cells:

Those numbers aren’t particularly pretty, and I don’t just mean that the charts don’t look good (I apologize for that, I work with large spreadsheets sometimes, especially when calculating wOBA’s, we’ll get to that in a second). When you see those totals, you can’t help but cringe. Even Gaby’s Southern League MVP season last year only translates into a .259/.334/.404 line, the epitome of league average hitting. He hasn’t exactly torn it up in his other years either. What do we make of this? How can it be used to project a number for this season?

Well, as always projections are rough to say the least. The best we can do is weight what we believe is closest to his actual current production. Knowing that, I used a common weighting system for each of his MLE years and came up with a weighted line for his counting stats. The weight places the most emphasis on the most recent season, with a weight of one for all counting stats on that season, followed by a weight of 0.5 for the season prior, 0.25 for the season prior to that, and so on, halving the weight for each season before the first. Using those values, I then normalized the projection for 650 plate appearances.

Of course, those numbers would represent projection including his 2009 stint in New Orleans. In order to be more true in projecting for this season, I did a projection using data only up to Gaby’s 2008 season, then I added his 2009 Triple-A MLE totals in 263 PA and added to it the projected totals normalized to a number of plate appearances such that the sum of the two would be 650. In other words, I did an in-season projection using Gaby’s Triple-A MLE.

Here’s what I got. Highlighted in teal is Gaby’s projection including 2009 data, while highlighted in darker blue is the total in-season projection adding 2009 data.

Here are the slash lines, strikeout rates, and walk rates, with the same highlighting code.

As you can see, both projections are about the same, and both aren’t very good. I’ll spare you my graphic for my wOBA calculator (I finally saved the wOBA formula on spreadsheet for easy reference, it’s much easier for doing these projections or other analysis), but it yielded wOBA’s of .306 and .304 for the including 2009 projection and in-season projection respectively.

Well, looking at that, there’s some good news and some bad news. The bad news is that neither of those wOBA’s begins to sniff good, or even league average. In fact, those border on replacement level. My projection also isn’t all that far off from some of the preseason projections done. Considering Gaby’s MLE production in New Orleans, Dan Symborski’s 2009 In-Season ZiPS projection sheet gives a .248/.309/.384 end-season line after around 640 PA. The in-season projection at that point would have yielded a wOBA of .307, right around where my projection was.

The good news, aside from the production STILL being better than Bonifacio’s this season, is that the projection systems we know and love don’t have that as Sanchez’s preseason projection. ZiPS, the example we used, had the lowest projection with a wOBA of .318 to start the year (.321 at my calculation, meaning they might be using slightly different linear weights or a slightly different normalizing factor than my generic 15%). As per FanGraphs, the other projections systems such as CHONE, Marcel, or Bill James’ system, had values for wOBA in the .340 range. But, if we buy these MLE numbers, how could we get a number that’s even close to .320? Well, while we certainly expect Gaby’s past performance to be a significant indicator of his success now, we can also expect to see some growth in his game, and the difference may indeed come in that. In our next installment, I’ll put Gaby through the same comp discussion I used with Chris Coghlna, based on swing, contact, walk, and strikeout rates found in this weighted analysis. From there we can establish perhaps some high and low comps, weight them accordingly, and see if we can’t project growth in Sanchez’s game.