Of course, the risk with trading is amplified: information asymmetry shifts from a player’s agent (on the free agency market) to a front office (in the trade market), which requires Stearns and the Brewers to maintain a different game theory (i.e., when making a trade, the Brewers cannot simply solve a coordination failure with another team by outspending all other comers); in addition to contractual risk, the risk of prospects or return assets must also be priced, which adds more room to strike a deal (“find the new market inefficiency!”) and to absolutely lose all value (the Jonathan Schoop and Andrew Susac / Phil Bickford trades are two examples of this for the Stearns front office).

There are several interesting trade partners across the league, including franchises that are tied to the Brewers’ front office personnel by lineage (as an example, Tampa Bay and Houston are probably the most prominent teams in this category). It would not be surprising to see the Brewers go after players that they are familiar with from Matt Arnold or Stearns’s previous organizational pipelines (or, whatever rumors those two can continually collect from the….er….informal information market). Recent changes across the league offer new trade opportunities as new eyes look over existing talent stock; here the Mets and the Giants most clearly come to mind. Additional rumors about rebuilding efforts in Arizona and Seattle, as well as the situation in Baltimore, add further trade opportunities for Stearns.

So who wants to deal? To make this article easier to read, the “Surplus Assumptions” are posted at the bottom of the article, as well as a Brewers roster (for full trade comparison).

First things first, everyone wants Jacob deGrom, so let’s take a look at the very best players that the Brewers could trade. At the top of this list, prospects like deGrom would basically require prospect packages like Keston Hiura / Corbin Burnes plus some filler; if the Brewers could acquire almost anyone atop this without surrendering Hiura, that would be magical.

To this observer, if the Mariners end up entering rebuild mode, the Brewers prospect package that could get the most mileage would be for a grouping of Mitch Haniger and James Paxton; this type of deal might be “lead” by Domingo Santana and Corey Ray if the Brewers also included a couple of their best arms. The price would be steep, but would bolster right field defense and On-Base Percentage (balancing the batting order, as well) and the starting rotation. Notably, this prospect cost would be roughly equivalent to spending one full market deal on Patrick Corbin.

There are also some players on this handful of teams that have gigantic contracts, and this is a place where Stearns could create a deal to “buy a prospect” or otherwise leverage the Brewers’ positive revenue scenario. The practice of “buying a prospect” basically means that the Brewers would take on the full balance (or significant balance) of a “bad” contract in order to receive a prospect from their trade partner. One example of this trade is how Atlanta acquired Touki Toussaint by “purchasing” Bronson Arroyo’s contract; to a lesser extent, the Brewers accomplished this when they grabbed Aaron Hill in the Jean Segura / Chase Anderson deal, which netted the Brewers potential impact prospect Isan Diaz (this was a great example of a “contrarian” deal by Stearns, as he acquired MLB talent during a supposed “rebuilding” cycle).

If Arizona is indeed rebuilding, a trade for Zack Greinke would be quite intriguing (someone like Corey Ray would fall right between his “raw” contractual surplus and total performative surplus). What is interesting is how many bad contracts the Orioles have; one would expect a creative rebuild from that organization, as they have so few valuable MLB assets that simply making solid trades for prospects will not be a clear option (at least not yet). It is interesting to imagine the type of trade the Brewers could make by retrieving Alex Cobb’s or Chris Davis’s contract from Baltimore. The Orioles are rebuilding, but their 2019 Top Prospect list indicates that there are nonetheless quite a few interesting players atop their farm system.

Finally, there is a group of very interesting trade targets that exist in a range of potentially cheaper prospect costs. I formed this group by looking at “raw” contractual surplus that would roughly cost an average prospect (50 Overall Future Potential), with total surplus that could range anywhere from average to impact prospect. One of the players on this list (Mike Zunino) has already been subject of a trade today:

Madison Bumgarner and Zack Wheeler are guys that jump off the page here for the “improve the starting rotation” types, and they are crucial examples of how tough it will be to price some veteran options. The range on Bumgarner’s value is quite extreme, and there is no way the Brewers would acquire the veteran southpaw close to his “low” price; so, the question would be whether one of the organizational impact prospects would be worth a player with quite a short-term contract horizon. Kyle Seager is another interesting trade candidate here, with a range that is almost impossible to decode into a useful prospect package: do you trade for elite Seager, or current Seager? What is the premium to be paid for his previously elite production?

Ironically, Jonathan Villar might be the Orioles’ most interesting and best available trade asset.

In short, there are plenty of intriguing players that the Brewers could acquire via trade. This exercise has hopefully opened a few of the strategies available to the Brewers (such as making a huge splash trade with prospects, or “buying” a bad contract). Additionally, the importance of being honest about high costs should also be apparent: the Brewers cannot simply “add an ace” if they view players like Keston Hiura as a part of their future, or even Zack Brown, Jacob Nottingham, Corbin Burnes, Brice Turang, and Trey Supak for that matter. Yet, in the event that the Brewers make a large trade, the pay off must be accurately assessed, which is one benefit of using a range of surplus assumptions to look at the high and low value markers available in a trade. For example, viewing Christian Yelich’s “raw” contractual surplus and total performance surplus below should show why it was worthwhile to surrender the prospect haul that Yelich required; the Brewers could conceivably do the same with an impact player for 2019, so long as the continued diminishing profile of their top prospects is assessed. If the Brewers forego a huge trade in the offseason, they could pay dividends both in terms of MLB development (in the case of prospects like Hiura), role determination (in the case of players like Supak and Turang), and more realistic roster need assessment during the midseason trade deadline.

Surplus Assumptions

To make it perfectly clear, here are my common surplus assumptions, with background here and here:

• Teams receive surplus value by retaining production and a contract (or, “scarcity”). Value in the MLB can be defined as the on-the-field performance and the scarcity of that performance (which is thus controlled by contractual terms).

• Surplus can be calculated in a “Raw” fashion, where the value of performance over time is simply assessed against contractual value; alternately, a “full” surplus assessment can be made by considering the future value on the field the club will receive, as well as the contractual hit they will take for employing that player.

• Arbitration and league minimum “reserve” contracts produce extremely high value because teams can frequently cut those contracts without paying full price. This adds value beyond the stipulations stated above.

• For this to work, MLB players, prospects, and cash must be translated to dollars. While this is an assumption that many do not like (opposing WARP/$ frameworks), I argue that the simple fact that teams trade prospects for MLB players, or cash, all the time demonstrates that these different asset classes can indeed be translated into a common currency.

• This should not be viewed as the be-all, end-all of player valuation, simply because there are different developmental models across organizations that could result in alternative models based on organizational strengths; WARP itself is only one way to measure players; prospect risk is nearly impossible to uniformly quantify across one group of players, which necessarily means that almost any prospect valuation system will be incomplete. Additionally, player development cycles are quite long, meaning that the value a player could be expected to produce within the next three years is nowhere near the value that could be produced in a decade; this matters depending on a team’s resources and the player’s distance from the MLB (or MLB service time), among other factors.

Here is one example of Overall Future Potential (OFP) pricing, based on a model that assesses all players in MLB history (to the point of that publication), and an update from 2017. These models will be further updated.

Based on these assumptions, here are the Brewers, including most of their players listed under contract at Cot’s Contracts, as well as a couple of their best advanced prospects (to compare prospect grading within the system). This article focuses on four calculations to produce surplus value:

• After depreciating production from 2014-2016, 2015-2017, and 2016-2018, those three figures are averaged to produce a “Blended Surplus.”
• The largest of the depreciated production from 2014-2016, 2015-2017, and 2016-2018 forms the “High Surplus.”
• “Immediate Surplus” takes a different look at production by simply using full 2018 performance and extrapolating it for three years. This is the equivalent of taking the most extreme view of immediate performance by a player.
• “Raw Surplus” is calculated by subtracting the average of these three figures, prorated for each player’s remaining contract, from the player’s contract (options excluded).
• “Surplus” is the final figure, adding the average of Blended, High, and Immediate surplus to the “Raw Surplus” contractual figure. This is equivalent to valuing a player’s on-field production separately from their contractual value.
• The “Raw” figure is meant to demonstrate a “buy low” price, and the “Surplus” column is meant to demonstrate a “buy high” price, but obviously these figures are not exclusive; they merely seek to establish potential boundaries for a trade.

Throughout the summer, I found myself repeating an argument about the Brewers front office: if the Brewers front office implements scouting, mechanical, and coaching adjustments with a given player, they have some form of prediction or forecast that forms an expectation for the impact of that adjustment. Consider the two major pitching developments for the Brewers, namely Jimmy Nelson’s delivery shift, pitch addition, and subsequent breakout, and Chase Anderson’s arsenal adjustment: given that the organization has kept biomechanical data for quite some time, it is reasonable to suspect that player development decisions about adding pitches or redesigning mechanics at the MLB level are data-driven to some extent.

Namely, if the Brewers front office understands that Nelson will change his delivery timing and throw a curveball, or Chase Anderson will shift his cutter and curve, they have some idea of the range of success expected by such a move. Even this is quite a conservative statement; given the amount of time invested in developing these players (for example, Nelson threw at least 640 innings before using a curve in 2015), a development such as adding a pitch or mechanical overhaul will not be taken lightly. It was my contention that the Brewers understood the benefits of these moves, and expected significant improvement because of these moves.

The flipside of the argument, which becomes more speculative and therefore much more interesting, is that the Brewers front office should be able to form a solid idea about the relative success or failure of a pitching mechanics or arsenal shift for a player. I gather that they should be expected to do the same for a batting mechanics adjustment, as well. This statement is not quite as radical as it sounds; it is not an inversion of “can” into “should” (where, “the Brewers can design data-driven formula to track the success of pitching mechanics and arsenal adjustments” becomes “the Brewers should be able to forecast the impact of mechanical and arsenal adjustments”). Forecasting involves the use of data collection, statistical methodology, and some form of modeling (this can come from relatively simple and straightforward measurements of change to more complicated methods such as linear regression, or ever more complicated methods still) in order to look at a series of projections and craft a statement about its most likely path; think about this in the way that Nate Silver encourages “probabilistic thinking” (providing a range of predictions instead of one), or the way PECOTA offers “percentile” projections and thousands of tests of any given season.

Granted, there are potential data issues that the ballclub could encounter (data could be incomplete and face additional questions of quality or collection errors, or the club’s analysts could make suspect decisions about the underlying concepts for their forecasts, etc.). Yet, that there are potential concerns with MLB data collection and forecasting should not be viewed as a reason to dismiss discussions of clubs’ forecasting expectations for particular mechanical adjustments; in fact, I’d argue that this is the whole point of an “analytical” movement in MLB front offices.

Stated simply, the Brewers front office probably had a very good idea of what their key pitchers’ adjustments would be worth on the field. At the very least, they should have forecast (and probably did forecast) the likely impact of those adjustments. At worst, if the Brewers forecast those mechanical adjustments and completely missed the breakout seasons, they now have additional data to expand their models. Now, they can return to their layers of data, and any previous forecasts, and investigate where their models succeeded and where they failed.

What the Brewers now have in Chase Anderson is a prototype: fans and analysts can break this prototype into any number of characteristics worth testing.

• Chase Anderson is listed as 73 inches tall and 200 pounds according to Baseball Reference; he throws with his right hand;
• he worked 418 MLB innings before his breakout;
• his breakout occurred in his age 29 season;
• he does not throw a slider according to Brooks Baseball; and so on and so forth.
• Each of these characteristics can be used to build comparisons with other MLB pitchers, in order to test lessons about Anderson’s arsenal and mechanical adjustments.

The trouble here, in terms of statistical theory, is that within the MLB there will be no randomized sample of a population of pitchers who could perform like Chase Anderson. Constructing such a sample would require meeting extremely narrow characteristics that already limit the underlying population. For example, according to Baseball Reference Play Index, 163 MLB expansion era pitchers were 73 inches tall, less than or equal to 210 pounds, and right-handed while working 100 or more innings during age-29, age-30, or age-31 seasons (limit that to age-29 seasons, and the list drops to 60; or focus instead on right-handed or left-handed pitchers, and that list expands to 231 pitchers; and so on). Luckily, there are statistical tools available for controlling for variables in a model that does not involve a randomized sample of a population.

Following the criteria listed above, here’s an example of pitchers most comparable to Anderson’s class, focusing specifically on the last two seasons. This will be helpful to begin the next installment of this series, which be an analysis of particular player acquisition targets for the Brewers:

Beyond the technical issues, an intriguing theoretical issue exists. Since one is ostensibly testing Anderson’s prototype in order to find another pitcher with similar mechanics, arsenal, or characteristics that could conform to the successful lessons passed to Anderson, we already know what we’re looking for (our pitching survey is biased). This is acceptable for one very specific reason: baseball players are extremely scarce, and pitchers especially approach the game with a relatively narrow set of strategies (the vast majority throw a fastball) and mechanical approaches (ex., the vast majority throw overhand), and rulebound constraints (delivery timing requirements, approach to the batter, etc.). Moreover, a front office is not simply “looking for baseball players,” they are “looking for baseball players that could be good,” or “looking for baseball players that could improve,” etc. What the Brewers can use their mechanical, arsenal, and coaching lessons to construct is a system, a system into which particular player prototypes can be included in order to apply lessons and logic of that system to coax future success. This is very obviously a difficult thing to do, and one should not expect an MLB front office to be successful in every case. Yet, one should expect an MLB front office to reasonably apply their successes to as many future players as possible in order to maximize those successful lessons (or even to improve upon, to build from player development failures).

In this way, assessing a pitcher’s mechanical approach is much like underwriting a real estate development deal: an MLB front office will have to make decisions based on extremely limited, or flawed, samples. Player acquisition and development is more akin to working within conditions of market failure than a perfectly competitive marketplace. Continuing the analogy, an underwriter for a multifamily project will not compare that project to single family homes, nor will an underwriter of an affordable housing multifamily building compare that project to a market rate multifamily set-up, and so on: there is a particular ideological approach and set of market constraints for each type of deal listed above, just as there are specific constraints for each class of MLB pitcher that can be evaluated. There certainly may be some scenarios in which assessing those real estate deals blindly and with an overreaching view is valuable (such as a regional land value survey), just as there may be some scenarios in which blindly assessing all baseball players would be valuable (ex., “What percentage of draft signees from the 2000s reached the MLB?”). But these conditions will not necessarily adhere to each particular transaction (and each particular player development decision is likely made with much more focused, narrow forms of knowledge, and much more problematic forms of data at that).

The Chase Anderson system can be applied to the 2017-2018 free agency, trade, and waiver classes, in order to answer one of the Brewers’ most difficult questions of the offseason: how will the club repeat rotational successes of 2017? How will the front office fill the void of the injured Jimmy Nelson? How will the club build on the success of Chase Anderson? Looking at these questions produces one of the most fun aspects of this coming offseason, for these questions can be addressed in a very particular manner by an openly analytical front office. What is especially fun is that when the Brewers eschew big name free agents (perhaps by necessity of market size, perhaps by choice) in favor of someone less well known, or perhaps more puzzling, fans and analysts should immediately look to the club’s prototypes in order to consider which lessons (from successes or failures) are being applied to the roster.

Photo Credit: Jeff Curry, USAToday Sports