Catcher Delousing

We blush with mortification when we contemplate how clueless we were as preadolescent stat geeks. This was back in the age of the glyptodons, of course, but even so, we lacked insight. As far as we were concerned, if Major League Baseball wasn’t measuring it, it didn’t exist. And since fielding statistics for catchers were essentially nonexistent then—really, all they had was fielding percentage (meaningless) and passed balls (the league leader was the catcher on whichever team had a knuckleballer, and everyone else was the same)—we knew and cared only about how catchers hit.

We thus well understand—indeed, as striplings we even played a variation of—a game described by Fred C. Harris and Brendan C. Boyd in their classic treatise of 1973, The Great American Baseball Card Flipping, Trading, and Bubble Gum Book. Their game was called Lousy Catcher. Its play consisted of one guy’s naming a “lousy catcher”—in other words, a second-string catcher who hit say, .240 or less with, say, 5 home runs or fewer—and the next guy’s trying to name a yet “lousier” one. As we recall, the player who trumped all others in Harris and Boyd’s divertissement was Charlie Lau. For us, it was Danny Kravitz.

Even aside from our failure to grasp how hard it is to play professional baseball, this was absurd on many levels. Charlie Lau, as you probably know, was a visionary hitting coach. Danny Kravitz (a) served in the Marines during the Korean War, and (b) is the only player, we think, whose first major-league home run was a walkoff grand slam with his team down by 3 runs in the bottom of the 9th. More to the point, they were both pretty good catchers. We just didn’t have the metrics we needed to gauge their performance.

Now, of course, we do. But here in Fantasyland, nothing much has changed. The incommensurability of meaningful statistics among the different fielding positions makes them virtually impossible to use for Fantasy Baseball. For those of you who, like us, would love to add fielding stats to your league’s palette, we offered a suggestion last year. But for us this season, and probably for you, it’s still 1960, and if a catcher can’t hit, he’s still “lousy.”

We were brooding about this injustice last weekend when we met our Fangraphs colleague, the debonair and perceptive Fantasy demigod Mike Podhorzer. Mike has discovered—we’re simplifying, but he’s published extensive explanations of this, and you can start with this one and then jump around—that any particular hitter’s Home Run to Fly Ball Rate in a given season is subject to random fluctuations that will regress in the following season to a rate more reflective of that hitter’s true home run power. He uses a complex equation based on the hitter’s fly ball angle, fly ball distance, and the standard deviation thereof to calculate the hitter’s Expected Home Run to Fly Ball Rate, and projects the hitter’s performance accordingly. This season, it leads him to, among other places, the conclusion that Matt Wieters will hit a lot more home runs than most people are projecting for him.

Looking over Pod’s list of players with HR/FB upside—in other words, guys whose xHR/FB exceeds last season’s HR/FB–we were struck by how many catchers are on it. This, in turn, led us to wonder: Can we use this to distinguish among lousy catchers? We’re talking about late-round, $1 guys here, so only a couple of home runs, all else being equal, would make a difference among them, And while we were at it, might Pod’s approach point us in the direction of other, less marginal catchers in addition to Wieters and Jonathan Lucroy, whom he also mentions?

We had to find out. So here’s what we did: We already had Pod’s xHR/FB percentages for all the catchers with upside. Then we went to Steamer’s 2016 Depth Chart projections. These are, to quote Alex Chamberlain, who wouldn’t lie, “a composite of Steamer and ZiPS [projections] with playing time allocated by generally informed Fangraphs staff,” not including us for reasons that are self-evident. We used these to calculate each guy’s expected Balls in Play by subtracting strikeouts from at bats. We multiplied that number by the guy’s career fly ball rate. This gave us his projected number of fly balls this season. We multiplied that number by Pod’s xHR/FB percentage, which produced a home run projection for each guy. We then compared xHR to Steamer’s projected HR to see who might be undervalued by the market, assuming arguendo that the Depth Chart projections approximate the market.

Here’s what we came up with. The first two numbers are the home run figures that we produced and the ones that Steamer projects. The next number is the player’s National Fantasy Baseball League Average Draft position. After that, we identify roughly—very roughly, so please don’t give us a hard time about it—the catcher to whose stats our guy’s would be comparable if you factor in the additional home runs. Then we tell you that comparable catcher’s ADP. First, the elite catchers:

 

Salvador Perez        22/17      ADP 98                 Kyle Schwarber (ADP 33)

Jonathan Lucroy    23/10    ADP 100               Buster Posey (ADP 20)

Matt Wieters            22/13     ADP 157                Brian McCann (ADP 109)

Stephen Vogt            22/13    ADP 162                Russell Martin (ADP 123)

Then, a couple of midpackers. We recommend tempering your enthusiasm for Hundley somewhat, since a couple of fly balls that would have been home runs in Coors last year will instead bounce off the enhanced right-field wall:

 

Nick Hundley              25/12    ADP 227               Travis d’Arnaud (ADP 137)

Francisco Cervelli      13/7      ADP 240              J.T. Realmuto (ADP 168)

Robinson Chirinos     21/13    ADP 315               Yan Gomes (ADP 174)

And finally, the objects of our quest–the Not-So-Lousy Catchers:

 

Josh Phegley                13/5       ADP 422              Miguel Montero (ADP 242)

Cameron Rupp           14/9        ADP 381              Jason Castro (ADP 319)

Caleb Joseph                 8/5        ADP 375              Dioner Navarro (ADP 360)

Tyler Flowers                9/6       ADP 467              J.R. Murphy (ADP 368)

Chris Iannetta              13/10     ADP 429             Montero

We’re going to be using these numbers for, at a minimum, tiebreakers for our backup and reserve-round catchers. We think you could do worse. But don’t thank us; we live to serve. Don’t even thank Pods; so does he. Thank Danny Kravitz.