Grading Trades: Surplus
Translating OFP
Cashing Out OFP
Organizational Logic and Playoff Trades

Over the course of the past year, I have used a WARP-based system to assess transactions. I use a harsh depreciation system to demonstrate the assumption that a player’s value will only decrease in time, which basically attempts to price trades closer to their worst-case scenario rather than their best-case scenario. I have priced prospects by assessing the distribution of 18,848 careers and using that distribution to approximate prospect value. This model employs Baseball Reference Play Index WAR data.

Assessing the careers across the history of baseball produces a clear distribution of talent, and also helps to clarify what a player’s ceiling looks like on the field. For example, by the time a batter reaches 1.1 WAR, they are within the top third of all batters in the game. This is helpful to temper expectations of how prospects should produce, and also to understand whether an MLB player is truly elite. Using this career wide scale to assess transactions ensures that analysts can quickly translate the distribution of talent to assess the likelihood of future player production (and therefore the risk of acquiring a player or prospect).

This scheme works across individual seasons, as well, which can be drawn from Baseball Prospectus CSV functions (for example, I found approximately 29,428 individual pitching seasons with recorded WARP, and thousands more with unrecorded WARP, and 95,790 individual batting seasons with recorded WARP, which can be assembled according to mean and standard deviation). Once the mean WARP for pitchers and batters is identified, one can easily scale nearly every player in baseball history according to their percentile on a season-by-season basis:

These scales can be used to approximate Overall Future Potential (OFP), as well, as the distribution between prospect classes can be compared to the distribution between historical seasons. For example, according to the 2013 Baseball Prospectus Top 10 organizational lists, those 300 prospects (and approximately 150 “just interesting” guys) are distributed as follows: 6.7 percent 70 OFP, 27.8 percent 60 OFP, 32.7 percent 50 OFP, and 33.3 percent 45-50 OFP (“just interesting”). In this scenario, 60 and 70 OFP prospects neatly align with the 1+ and 2+ standard deviation historical WARP seasons, while the 50 OFP prospects wind down to the mean WARP or fall just below replacement level on a single season basis. This should align with what one would expect a prospect to produce once they reach the MLB (for example, it would not be surprising if Mauricio Dubon was a player that accumulated between 0.0 and 0.7 WARP on a seasonal basis, while Josh Hader produced 4+ WARP at his best; we could certainly draw such estimates from their tools and scouting profiles).

By identifying mean and standard deviation for individual WARP seasons, one can assess player value in monetary terms based on the progression of each standard deviation:

I believe this is a useful, if crude, system because it seeks to provide meaning to a statement such as, “if Lewis Brinson is a star prospect, he will be likely to produce at least 28.0 WARP in his career;” alternately, one could reasonably expect Brinson to have a 4.0-to-6.0 WARP ceiling should he reach his optimal OFP. I depreciate this historical value in order to express the risk of Brinson reaching that level. Obviously, GM David Stearns and President Jon Daniels did not price out Brinson as a $196 million player (using one free market assessment of the value of WARP); however, depreciating Brinson’s ceiling to accommodate the risk that (1, at that time) Brinson failed to reach the majors and (2, perhaps more plausibly) Brinson plays closer to his floor than his ceiling in the MLB gets Brinson close to Jonathan Lucroy’s value. Placing Overall Future Potential (OFP), Wins Above Replacement (WAR or WARP), and contracts ($$$) on the same scale produces a solid at-a-glance pricing system that allows fans, analysts, and writers to quickly consider risk and reward. A similar price emerges if one moves from a historical career evaluation model to a model that assesses players based on their likely ceiling of seasonal WARP.

One benefit of assessing more than 18,000 baseball careers and scaling those seasons to prospect expectations is that the different parts of these systems speak to each other easily and clearly. We can literally test our assumption that the Lucroy trade was in fact a pretty good deal for both sides on the day of the trade. Obviously, post hoc analysis is necessary each and every year following a trade to test those assumptions. As in Benefit-Cost Analysis, it’s not simply enough to drop things the day of the trade, and adding analysis on an annual basis can help to fine tune assumptions about value, as well (or solidify trade deadline trends). In the case of the Rangers trade for Jonathan Lucroy and Jeremy Jeffress, depreciation analysis shows the rapid decline in surplus value that follows poor production:

Using WARP, OFP, and $$$ to assess trades is inherently problematic insofar as it (a) incorporates biases involving the Replacement Player Model, (b) only assesses players according to marginal value, and (c) assumes that player value can be expressed in one particular figure (be it cash, future potential, or current production). Yet, pushing back on (c), I don’t think it’s entirely problematic to say that an analyst can express player value at one point in time while also understanding how that value can change very quickly, on a seasonal basis, or over the course of a career. Jimmy Nelson is a fine example of this type of issue; the Brewers’ righty struggled with command and mechanical adjustments throughout his first couple of seasons, but working through adjustments has helped him produce notably above average runs prevention in 2017. It’s not wrong to assess Nelson in such a manner now (notably better than average), nor was it wrong to previously assess Nelson (struggling rotation depth). The narrative can connect to the statistics, and one can use a transactional model to assess risk and value in order to judge trades and perhaps understand how value is allocated within a given organization; one could even use such a system to analyze how an organization acquires risk (whether they are risk averse, or neutral, or aggressive).

It should also be clear that players can produce well beyond their OFP. Nolan Arenado is an example of such a player, a 50 OFP top prospect in 2013 who nevertheless entered 2017 with 21.9 WARP over four MLB seasons under his belt. But fans and analysts should be wary of the lesson of Arenado; for one Arenado, the 2013 Top 10 organizational prospects included 35 players with 0.0 or lower career WARP within the class of 50 OFP prospects (the same class as Arenado), and this is prior to considering the forty-five 50 OFP prospects from that class that had yet to reach the MLB (like Tyrone Taylor, for example). Arenado is a valuable lesson about how players can exceed their OFP, but one should understand that developing a single Arenado cost 80 players who have yet to reach the majors or are producing replacement level careers. Incidentally, the 2013 Top 10 prospects rated 50 OFP entered the 2017 season with 190.8 WARP over 287 seasons, which corresponds quite well to the mean seasonal 0.46 WARP produced above.

Both WARP and OFP have their respective imperfections as measurement systems, but their benefits also allow them to serve as solid transactional assessment tools despite their shortcomings. In the case of the Brewers, one can literally price out the value of the club’s extra cash, surplus of prospects, and the depreciated (or maximum) surplus of any intended trade target in order to understand whether a trade is worth the risk. Absent databases full of proprietary scouting, mechanical, and health information, this type of at-a-glance measurement system can approximate transaction prices and help one understand whether teams made an advantageous trade, or simply a good baseball deal.

• Eric Thames, nearly a handful of years removed from the MLB, previously a Korean Baseball Organization superstar, translated his overseas success into strong MLB value for the club’s $16 million gamble (1.9 WARP).

• Travis Shaw, a sometimes-platooned third baseman caught in a packed Red Sox infield, flashing his potential as a full-time player (1.4 WARP).

• Jimmy Nelson, a previously middling innings eater in the rotation, now two new pitches and mechanical changes deep into his career, showcasing a solid new look on the mound (1.1 WARP).

• Orlando Arcia, the club’s former top prospect from the 2015 Biloxi breakout, now materializing that fantastic glove on the MLB diamond as the bat develops (1.1 WARP).

• Manny Pina, a former Player To Be Named Later, emerging at the catcher position due to the prolonged absence of Andrew Susac and a gamble on his late 2016 “breakout” (1.1 WARP).

• Corey Knebel, a formerly hyped “high leverage relief” prospect acquired way back in the Yovani Gallardo trade, now receiving a chance to showcase that electric stuff under the microscope of the closer’s role (1.0 WARP).

I do not have one doubt in my mind that if BPMilwaukee, or anyone, really, ran a series of preseason articles claiming that this six-pack of players would lead the Brewers to the top of the division into June, that would have been dismissed as much worse than wishful thinking. Yet, here we are, a gang of unsung players and a couple of hyped prospects are leading the Brewers and creating fantastic value. These six players comprise half the club’s wins above replacement value.

Related Reading:
Cashing Out OFP
Bandy-Maldonado
Aging Braun

Yet, if one compares the current production and contractual status of the Brewers’ major contributors to the preseason surplus expectations, one can find that the expected leaders heading into the season have also been quite strong for the Brewers. Essentially, the vast majority of the expected leaders entering the season have continued to provide value for the roster while another set of depth players are surpassing their expected surplus and that surprising set of leaders paces the WARP rankings.

The following table showcases the Brewers’ current production, compared to their preseason depreciated surplus value. Depreciated surplus value calculates a player’s three-year production basis at 70 percent value, and then prorates that depreciated figure according to the player’s contractual situation. The goal is to project a player’s future production on a declining scale, rather than an optimistic scale. In order to project current value, I also created an expanded depreciated surplus metric, which calculates a player’s 2014-2017 production, basically expanding the three-year model to a 3.33 model. To compare depreciated and bullish models, I also simply projected a player’s value if they maintained peak 2017 performance for the remainder of their contractual reserve. Money is not figured into arbitration or league minimum (reserve) contracts, since those players ostensibly cost the club nothing to release (ex., arbitration eligible players can be non-tendered between seasons at no cost, and the cost of releasing a league minimum player is negligible). For players age-26 or younger, I added an Overall Future Potential (OFP) valuation (Thames has a preseason OFP valuation to express the inability of assessing his expected talent level).

Compare that ranking with the 2017 surplus value leaders entering the season; this is probably the group of players that fans and analysts reasonably would have expected to lead the club. Veteran Ryan Braun and newcomer Junior Guerra have not been bad, but both missed time with injury (0.8 WARP); Jonathan Villar and Zach Davies have struggled to varying degrees (although Davies’s Sunday start against the Dodgers was an exclamation point on the idea that the righty was heading the proper direction) (-0.6 WARP); Travis Shaw is materializing his surplus value and serving as one of the production leaders (1.4 WARP); and Carlos Torres, Hernan Perez, and Keon Broxton are generally serving as valuable depth (1.7 WARP).

Entering the season, this group of players represented $235.8 million in surplus value, which vaguely cashes out into 33-to-34 MLB wins (those wins can be long-term or short-term, obviously depending on when GM David Stearns decides to cash them out); adding the updated “extended depreciated surplus” metric results in $253.2 million in surplus value, or 36-to-37 wins. What is thrilling about this development is that this group of players averages 3.7 years of contractual reserve, meaning that the club has another chance to return many of these players to try and advance this roster once in another year. The actual depreciation of these roster assets has suspended for a year, and the value of these players to the organization is higher because they have improved as a group.

Surplus value is obviously quite an abstract and contentious measurement. First, one can define both scarcity (of a skillset, or service time, etc.) and production in many different ways. Even if one were settled on the idea that “value = production + scarcity,” questions about whether to depreciate a player’s expected production going forward, or to use a player’s maximal outlook, and every question inbetween, would render that equation of suspect meaning.

Even with this caveat in mind, I want to suggest that one of the reason the Brewers are successful in 2017 is that Stearns has capitalized on players that maximized their surplus value in short order. Basically, this group of players have largely staved off any immediate delivery of depreciation, which is thrilling for the roster core and the trade deadline. It would have been ridiculous to suggest that perhaps Jett Bandy could produce enough value to be flipped for a 50 Overall Future Potential (OFP) prospect by the deadline, and perhaps even more bullish to suggest that he would materialize as a long-term quality depth catching option. The same might go for Jacob Barnes or Domingo Santana or even Eric Thames (who would probably be very difficult to trade, in terms of finding a prospect partner that matches his divisive historical profile and approach to the game). This is one way to cash out the improved surplus scenario for the Brewers; but one can also simply say that Stearns has successfully assembled a gang of players that produced three-to-four additional wins in organizational value thus far.

In Out of the Pits: Traders and Technology from Chicago to London (University of Chicago, 2006), Caitlin Zailoom presents an ethnography of commodity markets that demonstrates the embodiment of these markets, as well as the gendered, strategic, and technological standpoints that define commodity markets in space. While many understand the market truth of “buy low, sell high,” most do not dig any deeper than that truism into the strategic forms that materialize that mantra for shareholders. Zailoom demonstrates two specific strategies that allow commodity traders to maximize value: scalping and spreading. A “scalp” is a trade that seeks to immediately capitalize on an asset’s value, while a “spread” strategy focuses on taking offsetting short and long term positions to deliver profitable returns. Both of these strategies are applicable to Stearns and the Brewers front office for the trade season, which many fans are falsely equivocating into “win now” or “continue the rebuild” categories; rather, Stearns can move in several contrarian directions in order to maximize the Brewers’ current and future value.

Scalpers are a fascinating type. Zailoom writes, “local traders hope to profit from correctly predicting the movements of the market up or down and risk losing their own money in the process. They are speculators in the most pure sense — individuals making money purely on the changing prices of financial commodities. Although locals have a variety of trading strategies, most of them are known as ‘scalpers.’ Scalpers trade in and out of the market within seconds or minutes, profiting from small price fluctuations. Making hundreds of trades during the course of the day, the scalper never goes home owning contracts” (p. 62). Obviously, the metaphor of going home without owning contracts cannot apply to a baseball team, but the spirit of quickly capitalizing on moving prices might be applied to many of the players reserved on the Brewers roster. A “spread” strategy most certainly can be applied to baseball trading cycles: “A spreader takes opposing positions in each of two instruments, using the more stable contract to limit the loss potential of a position in the more volatile product” (Zailoom, p. 86). This type of strategy might be ascribed to the notion of “trading from depth,” which ostensibly means that the club is mitigating production volatility by “selling” a player from a position of strength (which therefore equals less organizational risk) in order to “buy” production for another area of the team (ostensibly shifting short-term risk to this acquisition).

A brief visualization, where ‘X’ are the Brewers, and the Brewers are trading with two partners in separate transactions (Team Y, Team Z) involving Overall Future Potential (prospects) and WARP (MLB players) that may be cashed out over an unknown period of time:

Stearns can essentially (1) hedge three-to-four surplus wins created with the MLB roster (basically keeping this as “cash in hand” or “organizational collateral”), (2) trade a “less valuable” MLB player while the iron is hot (a “scalp”), and (3) trade valuable prospects for a more valuable MLB player. This sequence might be the equivalent of flipping a player like Domingo Santana to an American League club (maximizing his offensive value and mitigating his defense), while also trading multiple prospects for a controllable starting pitcher. This is an extremely risky series of deals, but exogenous to the model are those three-to-four surplus wins that essentially mean Stearns really is playing with house money (a familiar theme here at BPMilwaukee).

Consider the Brewers’ current catching depth to demonstrate a scalp and spread. Given the injury status of Andrew Susac, and the relatively slow development of advanced prospect Jacob Nottingham, the position is not necessarily a true position of depth for the organization (especially given the physical toll of the position). Yet, there are other stateside prospect assets around the organization (from Dustin Houle to Mario Feliciano to Jose Sibrian) that could conceivably build a pool of prospects large enough to offset risk of short-term moves. Stearns could “scalp” the monstrous surplus gains of Jett Bandy, which would be about as short a turnaround as one could provide in baseball (ex., a trade in two consecutive “windows,” consecutive offseason to midseason windows). Pina, Susac, Nottingham, Houle, and waivers would provide the most immediate risk mitigation here, with low-ball prospects potentially providing the greatest long-term payout to this strategy for Milwaukee. A “spread” move could see the Brewers buy- and sell- in different directions, depending on available moves to maximize club surplus; it should not necessarily be surprising to see Stearns deal some prospects and also deal some MLB depth. Faced with a roster that has already added up to four wins in depreciated surplus value, and a farm system overflowing with prospects, Stearns can “cash” those four wins in a variety of ways.

Adding layers of deals, the Brewers can take “spread” positions across MLB and minor league levels. Perhaps this means using one deal to trade a flyball prospect (like Trey Supak)…

…and another deal to return a groundball prospect, while using additional deals to return MLB rotational and bullpen depth:

The point is not necessarily to dig into specific players here (really, nearly everyone except for a handful of players should have a transaction value for the organization). Rather, the point is to demonstrate that using embodied market strategies can help transcend the “win now” / “continue the rebuild” trade conundrum that is currently consuming Brewers fans and analysts. The Brewers need not do anything other than return maximal future surplus and present surplus with their MLB players and prospects. Thus may we enter “neverbuilding,” or “counterbuilding supreme”: with significant organizational collateral in hand (three-to-four additional surplus wins) Milwaukee has an opportunity to continue competing in 2017 while transcending the “win now” and “win never.”