I often recommend The Roger Angell Baseball Collection for iBooks. It’s a digital compilation of Angell’s three most widely acclaimed collections of baseball essays (The Summer Game, Five Seasons, Season Ticket) that you can get for $20. I bought it last fall, and am just closing in on finishing it. (Having three kids under the age of four does not permit one to read for pleasure as much as one might wish.)
Strung together, the books trace baseball history from the dawn of the expansion era to almost the end of the 1980s, and because of the way Angell observes and relates the game (as a passionate fan, but an interested, educated, and engaged one, with no aspect of the action or the off-field shenanigans unworthy of his examination), the collection offers a fascinating look into the rhythm of baseball history—where it repeats itself, and where something wholly and honestly new develops.
One thing Angell mentions multiple times is the ever-increasing difficulty fans face in keeping all the league’s characters and characteristics straight. He dutifully reports on the rate of franchise movement in the 1950s and 1960s, and on the ballpark turnover in the 1960s and 1970s. He also discusses the way expansion (which happens three separate times during the span covered by the collection, adding 10 teams to what was a 16-team outfit when he began) cluttered the landscape and took away fans’ ability to know the opponents coming into town, to guess along with the manager, and to keep a mental encyclopedia of detailed data on the whole league.
It’s one reason why his essay in praise of the MacMillan Baseball Encyclopedia is one of the most joyous accounts in the bunch. He’s that happy to have a resource to use to keep track of the suddenly unwieldy world of baseball, past (because the game was young, really, when Angell began writing, and you can feel him fighting to hold onto the picture-perfect command of the historical record as the years pass and that record roughly doubles in size) and present.
Even now, with the internet having largely saved us from feeling unfamiliar with anyone in whom we actually have interest, Angell’s gentle laments ring true. We don’t know some details about modern players that fans used to know about virtually every player on their hometown team. For instance, I know that Anthony Rizzo switched to Matt Szczur’s bat during the playoffs last year, and that he did so because Szczur’s bat was slightly smaller and Rizzo had felt his bat speed slipping as the season wound down. I could not tell you, though, whether Rizzo’s bat is larger or smaller than the average player’s, or even the average player of his general profile, and I certainly couldn’t tell you the exact dimensions of the thing.
I know, from simple observation, that Javier Baez uses a very small bat. He sometimes seems to be wielding a billy club, rather than a full-sized bat. Still, it’s something we used to know about almost everyone. Angell talks about the bat sizes and preferences of a number of players during his perusals of various teams, even some in whom he takes only a passing interest while covering spring training. I remember knowing the exact weights of Sammy Sosa’s, Mark McGwire’s, and Frank Thomas’ hardware during their peak seasons, and about details like the way Moises Alou shaved down the handles of his bats to suit his unique grip and wrist actions.
I wonder how protective players would be of this information, if asked for it. It seems like it would be an easy thing for beat reporters to find out, and if someone took up the job, it seems like something we could easily catalog online. Then, if a given player used a bat much larger or smaller than other players of his ilk (size, swing path, plate discipline, etc.), we would be able to note it and ask informed questions about it. We would be better at noticing things like hitters switching to lighter or heavier bats, and we would eventually be able to estimate the actual value of making such a change.
We’d be able to link data about bat size and weight to exit velocity and launch angle, to see whether that’s an important, independent variable. I suspect that, in the long run, we’d identify players who have tinkered and tried out different bat sizes, but still settled on ones that are suboptimal for them. I suspect teams do some version of this already, but we might still find some players whose bats are an inefficient fit for their skill set.
Most importantly, a careful study of the importance of bat size might help in the evaluation of amateur hitters. If a guy has elite bat speed, but it comes from using an aluminum bat, scouts already account for that. They’re suspicious, until they see a player succeed with wood, and if they don’t get to see that, they make mental adjustments to their opinions based on the difference between metal and wood bats. Surely, though, some high-school kids are using the wrong bat.
One might be using a bat that’s too light, and therefore getting into bad habits that will be punished when he switches to wood. Another might be using one that’s too heavy, or too long, and therefore looking slower through the zone than he really can be. The more we know about how the optimal bat size correlates with body type and skill set, and the more carefully we track who’s swinging how much stick, the better we could identify players whose amateur showings are particularly distorted.
A good carpenter never blames his tools, but he also doesn’t trust them blindly. Hitters’ top tools are their bats, and they obsess over getting them just right—from dimensions, to grip, to weight balance. They even do things that probably have no real efficacy, like passing the barrels of the bats under heaters on cold nights, trying to get their lumber ready to deliver maximum force to the ball.
It’s very hard, in this time when dugouts have become stuffed with proprietary information and fans are held a bit more at arm’s length by the practitioners of this art (and when there are so many of those practitioners, in the big leagues and in the minors), to keep tabs on details like these, and to amass objective data that can help us learn from them. Still, it might be worth doing.