Great Moments in Yahoo! PBP

Today Yahoo! unveiled a completely new design for their MLB page. Alas, the PBP now reads backwards and is as ill-equipped to deal with unusual plays as ever:

The Only Rule Is It Has to Work

Note: The following is a rare (for this blog) timely book review.

The premise of The Only Rule Is It Has to Work is that respected sabermetrically-inclined authors and podcasters Ben Lindbergh (Baseball Prospectus, Grantland, Five Thirty-Eight) and Sam Miller (Orange County Register, Baseball Prospectus) were given the opportunity to act as the baseball operations department throughout the 2015 campaign of the Sonoma Stompers, member of the four-team Pacific Association, a low-level indy circuit in northern California. Lindbergh and Miller were granted wide berth to put their mark on player acquisition, roster construction, and in-game strategy, and also attempt to bring modern data collection tools (PITCHf/x, video scouting, etc.) to the bush leagues.

Lindbergh and Miller are embedded deep within the team--in the front office, the clubhouse, the dugout, and even (for a moment at least) kangaroo court. Thus it serves as one of the most revealing examinations of daily life in baseball from an outsiders' perspective. Most books that have provided similar access to the inner workings of a team have been written by insiders, even if they might not fully fit into the world in which they have spent many years (think your Jim Boutons). While the life of an indy-league player is certainly less lavish than that of a big leaguer and perhaps less structured than that of an affiliated minor leaguer, it's hard to imagine that the basic human impulses of (largely) twentysomething, athletically-gifted ballplayers varies much between Sonoma and San Jose, San Jose and San Francisco. The authors are able to observe the scene with some combination of bemusement, paternal-ish concern, and comradery to give the audience a different perspective on the people who play the game. Certainly the majority of the audience members can better relate to the authors' stations in life and can now imagine how they might fit in (or not) if thrust into the life of a ballclub.

While it should hardly be necessary at this point for sabermetricians to defend themselves against scurrilous charges of not watching the games, one thing that the authors don’t reflect too closely upon but that is obvious to the reader is just how much low-level baseball they watch over the course of the summer, and just how devoted to their cause they are. Granted, Lindbergh and Miller are aided by a small network of volunteer scouts that earns the derisive nickname "The Corduroy Crew" around the league, but one or the other personally does advance scouting of nearly every game the Stompers' opponents play. This in addition to the hours spent researching potential players with their proverbial noses buried in a spreadsheet. While it would be wrong to hold Lindbergh and Miller's labors (which of course were performed with at least the secondary intent of providing fodder for a book) up as a pure representation of baseball love to be extrapolated to all of their sabermetric compatriots, it would be less wrong to do so than to brandish the common stereotype.

One of the disappointments of the project is that many of the radical ideas the authors dreamed about being able to test are never put into play. While shifts and flexible usage of the relief ace take hold in the second half of Sonoma's season, batting orders largely remain tethered to convention, starting pitchers still generally work in rotation, and the manager holds on to ultimate in-game command. While this may be disappointing to the reader longing for sabermetric red meat, the implications raise questions worth considering. Is it necessary for change in baseball tactics to come one easily digestible piece at a time? Why can a grizzled bench veteran and former pennant-winning manager of a major league team (Clint Hurdle) pivot to the approach his superiors' desire with more aplomb than a 37-year old pot-smoking player-manager who goes by Feh and dabbles in 9/11 conspiracy theories? Do the high stakes of the majors actually make them a more suitable laboratory for experimentation, as players and managers can count on their million dollar checks regardless of whether they may look unconventional on the field? While these questions can't be answered by the book, it provides some entertaining anecdotal evidence to consider.

Along the way, the Stompers inadvertently break ground in the social realm of baseball as well, as one of the authors' hand-picked college signees, relief ace Sean Conroy, comes out as the first openly gay player in professional baseball. The authors do an excellent job of relating this part of the story without falling into self-congratulations or allowing it to swamp the baseball portion of the narrative. Lesser authors with a less interesting baseball story to tell (and perhaps less respect for their subject) could have easily allowed Conroy's story (which includes being one of the Pacific Association's most valuable pitchers) to crowd out other aspects of the Stompers' season in the narrative, and could hardly have been blamed for it.

The authors alternate chapters, and if you are a regular listener (as I am) of their Effectively Wild podcast, you will likely be able to pick out which voice you are reading after a couple of pages even if you forget for a moment whether it is an odd or even chapter. Lindbergh's earnest verbosity and Miller's cheerful nihilism carry through to the written page in book format yet complement each other well, imbuing a diversity of style to the writing while still making you feel as if you are reading the same book.

As luck (or the residue of design) might have it, the story has a dramatic conclusion that I will not spoil here, except to say that I'm very glad the majors have resisted the allure of the half-season format, except for every ninety years when unusual circumstances take hold (if I live to see baseball in 2071 I promise to be grateful and not complain about it too much). Were it ever turned into a movie, the scriptwriter would even have something of a "pick your own adventure" opportunity to affect the outcome with only the proverbial flap of a butterfly's wing.

And maybe that's one of the lasting lessons to take away from The Only Rule Is It Has to Work. That despite the careful planning, the on-the-fly adjustments due to injuries or player poaching (at this level), the dedication of the players and support staff, the superstitious rituals, and the motivational speeches that are poured into baseball clubs, not to mention the attempts to drag baseball kicking and screaming into the sabermetric age, we will never be able to escape what seem from our imperfect perspective to be random rolls of the die.

LWR Component Deflators and Replacement Hitters’ Batting Lines

Last time, I explained how we could use Linear Weight Ratio, an offensive metric developed by Tango Tiger, as a shortcut in finding a variable which I call the “component deflator” and symbolized as “a”.

Last time I focused on its application to park adjustments, but that’s not necessary. In fact, the component deflator can be applied generally to any situation in which you’d like to know what across the board percentage change in mutually exclusive offensive events would you have to see in order to alter run scoring by some scalar (assuming you are willing to accept that the linear weight values stay constant, which is certainly an assumption that must be applied with care).

So there are any number of questions that this kind of approach can address. One that I will consider in this piece is “What would a replacement-level hitter’s batting line look like?" First a few caveats, though. As Tango has pointed out, there really is no such thing as a replacement-level hitter. A replacement player is a replacement player because his overall contribution, offense and defense, is at a level so as to have no marginal value. Thinking about it in terms of a replacement level hitter only confuses the issue.

However, the analytical structure of assuming that replacement level players are average in the field, and thus calculating their value as their offensive contribution above a “replacement” performer specific to their position plus their defensive contribution above an average performer at their position can be a useful approximation. It is the structure used by a number of approaches, including Pete Palmer’s TPR (which is above average, but the same principle holds), Keith Woolner’s VORP, and the RAR figures I post here at the end of each season. I am not claiming that this approach is optimal or superior to the others, only that if applied with caution it can be a useful model of player value.

For the sake of this post, let’s just assume that we are going to use a model where a replacement level player hits at some percentage of the league average. Then, if we’d like to know what his batting line might look like, we can use the component deflator approach. The good thing is that we don’t have to worry so much about the fact that we have static linear weights, since we are now applying the process to individuals for whom we’d like to hold the weights constant (ignoring the Theoretical Team arguments). So that caveat is loosened in this application.

Of course, this approach carries some of its own caveats with it: one is that we are again developing a model in which all events are equally deflated. It might actually be that replacement level hitters tend to not be as deficient in BA as one might expect. Or maybe teams are willing to trade BA for power in a replacement level hitter. This is a specific model with specific assumptions, and it is not necessarily reality.

Anyway, if we define R as the percentage of league average (or positional average or anything else if you’d like), then we can just plug it into one of the formulas from last time, and carry out the rest of the calculations as explained in that post:

New LWR = ((LWR/s' + x)*R - x)*s'

In my RAR estimates, I assume that a replacement player’s R/O is 73% of the positional average, where the positional average is figured by taking the overall league average times a long-term offensive positional adjustment. The positional adjustments I use are (note: you can tell how long ago I wrote this by the use of 2008 league totals):

C = .89, 1B/DH = 1.19, 2B = .93, 3B = 1.01, SS = .86, LF/RF = 1.12, CF = 1.02

Combining these adjustments, the LWR component deflator procedure, and the overall 2008 MLB offensive averages, here is the offensive output expected from a replacement player at each position:



How do these numbers look to you? My impression is that the batting averages are too low; teams may resort to replacement level players at 73% of league R/O, but they may be those that trade secondary skills for BA points of equivalent value. (assuming that players of this profile even exist in reality)

Anyway, you don’t have to take any of this too seriously, and I’ve already stated that the assumptions and admitted they may not model reality, so I’m not going to spend too much time justifying the results. Instead, I have another potentially amusing if not completely realistic application.

Namely, it is to take the initial statistics of a real hitter, and maintaining the proportional relationships between his positive events, projecting what his line would look like at a different level of productivity. For example, what would a replacement level hitter with Barry Bonds’ bizarre 2004 proportional relationships look like?

In this case, I’ll assume that a replacement player would have a 3.50 RG. Bonds’ 2004 line comes out to a 18.26 RG, so our “R” will be 3.5/18.26 = 19.2%. This line results:



The bizarro Bonds would hit just .140, but would still manage to put up a .416 secondary average. Of course, such a player would never really exist, but if he did, his offensive value would be about the same as the other replacement level guys above.

Let’s look at Tony Gwynn, 1994 to see what this would look like for a very good singles-type hitter:




And we could try going the other way. What would Mario Mendoza, superstar look like? Here’s the transformation from Mendoza’ career line to a 8 RG:



In order to turn Mendoza’s no-secondary skills profile into an all-time upper echelon great, you have to allow him to hit .400, and increase all of his positive rates by 81%.

This translation approach falls squarely under the category of "toy"; please don’t get the impression that I’m elevating it to any greater pedestal.