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.

• MLB production by known assets will frequently be valued more so than unknown production by future assets (even where numerous scouting accounts and talent assessments are available).

• Trades involving MLB players and prospects will be difficult to assess because immediate production at the MLB level requires a different scale for assessment than numerous contract reserve years for a prospect.

• The existence of six-to-seven years of contract reserve rights for prospects will tempt analysts to value length of control over quality of production (ex., the Brewers traded Martin Maldonado, a superior player, for Jett Bandy, a player with a potentially similar profile but more risk as well as more “control years”).

• Analysts, fanbases, and probably even teams will be biased in favor of the value of the players that they currently reserve within their system and undervalue the players that are outside of their system.

Throughout the 2016 season and 2016-2017 offseason, I worked on a Benefit-Cost Analysis style pricing system that sought to place MLB Wins Above Replacement Player (WARP), prospect/role Overall Future Potential (OFP), and cash ($$$) on an interactive scale. The culmination in this system was my “Translating OFP” article, which hypothesized that the potential value of a prospect could be calculated by categorizing historical baseball performances. By taking the broadest picture possible (indeed, calculating the WAR/WARP surplus for 18,000 batters and pitchers), I ascribed monetary value to specific prospect classes. Since these classes are interactive, they can effectively be used to test various assumptions (for example, if one wishes to calculate a player’s full range of 40 OFP-floor-to-60-OFP-ceiling, like the case of Lucas Erceg, one can average that full range of values; or, one can simply focus on highest possible ceiling, likely middle ground, etc., for prospects).

The point is not that there is one way to assess prospects, nor that player value is solely transactional. Instead, the point is that since MLB teams do in fact engage in rebuilding or win-now strategies at varying points in their franchise tenures, and do in fact trade minor league players for MLB players (and vice versa), these player types are indeed interactive even where their value is placed on entirely different scales. Taking inspiration from Benefit-Cost Analysis is important, then, as one can understand that the economic value of logging can indeed be assessed against the value of endangered species that reside within a particular logging habitat, or that the cost of a highway can be assessed in terms of fiscal impact, shipping improvements, commute time improvements, safety for drivers (expressed reducing preventable deaths), etc. Once again, these types of metrics are not absolute, which is why reasonable Benefit-Cost Analysis procedures include post hoc assessments to review assumptions and actual asset performance (compared to expectations). The same can be done for MLB players and minor league prospects insofar as front offices do indeed transact for such players.

Series & Revisions:
Translating OFP
OFP and Minor League Pay
Revisiting the CC Sabathia Trade
Cashing Out OFP 2
Organizational Logic and Playoff Trades
Historical WARP and OFP

In a forthcoming post, I will present an update on the 2013 Baseball Prospectus Organizational Top 10 lists, which I began tracking this season in the hopes of designing a realistic time series assessment of prospect value. The ideal in developing this approach is to answer the question, “How do prospect classes progress over time?” A related question can then be answered: “How do prospects of a particular OFP perform over time?” By the time 2017 started, clear delineations between 50 OFP (average), 60 OFP (first division), and 70 OFP (superstar!) prospects were already forming at the MLB level from the 2013 Organizational Top 10 class. These classifications further solidified during the 2017 season, and the benefit is that there are now five full seasons from the publication of this list through which player value can be assessed.

From the 2013 prospect class, I constructed the following table comparing each prospect category to the average MLB performance from that class, and used those figures to determine a monetary “price” for those prospects and MLB production. The difference between each OFP category and the average production from the full prospect class can create a WARP figure that can then be “monetized,” thereby translating OFP into a WARP category. “Risk” (based on each OFP category’s frequency of reaching the MLB) can also adjust these WARP and monetary figures. In this case, however, OFP production value is concrete instead of speculative; this is what certain OFP classes actually did at the MLB level (the same goes for these risk classifications, which are also “actual”):

Assessing 756 MLB seasons, played from 2011-2017 (with most prospects playing between 2014-2017) by the 2013 BP Organizational Top 10, allows for a broad range of data to be analyzed. This produced time series for each player that can be analyzed, as well as annual summaries and prospect class summaries. From this table, one can compare initial historical OFP estimates with risk-oriented “bare minimum” prices and “top ceiling” prices:

The same criticisms of using WARP and OFP to assess players obviously apply: MLB players and minor league prospects are dynamic, and at different points of time their WARP or OFP may indeed mean different things; a player can add a new pitch or make a delivery adjustment and improve upon their previous performance (like Jimmy Nelson), or answer a specific set of approach and mechanics questions to achieve a higher grade (compare Josh Hader’s 2013 Top 10 appearance as a 50 OFP Orioles prospect with his 2017 Top 10 appearance as a near-surefire impact MLB player between 55-60 OFP depending on high-leverage relief or Number 3 starter risk assessments). For 2018, Brewers CF prospect Monte Harrison will be a great example of a prospect whose OFP role has evolved over time, due in part to injuries and also in part to on-field adjustments and advancements; Corey Ray will almost certainly demonstrate this fact in the opposite direction, due to mechanical question marks and growing pains.

So, indeed, WARP and OFP should not be viewed as fixed, or definitive metrics. They should be viewed as reasonable snapshots of a player’s value or potential at a given time, which MLB teams can indeed use in order to assess transaction value. A common complaint about my method is that MLB teams do not use WARP and OFP to assess players, but I find that this complaint misses the point that teams do boil players down to a “number” when they decide to trade, or keep, a player; their “number” might be predicated on a blend of proprietary scouting insights, years of mechanical data, and other performative metrics. That MLB teams do not use WARP and OFP to assess trades does not mean that fans and analysts should not use these metrics where other proprietary information is not available; for failing to capitalize on the interaction between Future Potential, Replacement Value, and cash means that the MLB analyst and fan missing one specific constellation with which transactions can be assessed.

Photo Credit: Steve Mitchell, USAToday Sports Images