Last off-season I began work on a framework that would better explain how front offices performed each season by utilizing a couple of frequently used economic measures. My goal was to gain a better understanding of how general managers performed other than, “their team won this many games” or “they went so far in the postseason.”

I suggest you read the full article for a better understanding, but long story short I used economic profit and gross domestic product (GDP) as the basis for the metrics. Instead of dollars I used wins above replacement (WAR) as the form of currency. I realize that WAR is not perfect, but I needed a measure that I could use across multiple entities such as batters, pitchers, and teams.

I reconfigured economic profit and GDP so that it would be conducive to measuring baseball players and teams. Out of that reconfiguration came economic WAR (eWAR) and gross domestic wins (GDW). These measures are calculated in a similar fashion to their counterparts, but a few slight adjustments had to be made in order for them to be more applicable in a baseball environment.

A brief explanation of eWAR:

Economic profit is the basis for eWAR, and in an economic sense it takes into consideration the lost opportunity cost of an investment or transaction. It is the intrinsic value that one would calculate. The accounting profit is the actual value. In my baseball version of the concept, total WAR takes the place of accounting profit and eWAR takes the place of economic profit. So instead of just looking at total WAR to evaluate a teams’ performance, we can look at the intrinsic value, and by doing this, account for the lost opportunity costs of players traded, released, or in some way removed from the team

The formula for eWAR:

eWAR = Total Team WAR – WAR of Players Exported from the Team

Below is the 2015 eWAR for each major league club.

The top spot goes to Jeff Luhnow and his staff in Houston. This is not too surprising considering Houston was one of the better teams this year. Their only exports that had a positive WAR for their new teams in 2015 were Dexter Fowler, Anthony Bass, and the great Matt Albers.

For the most part, the good teams are near the top of the eWAR list, but there are a couple of teams that made the postseason which are not near the top. There could be a few reasons for this, but let’s first take a look at the rankings for the second measurement: gross domestic wins.

A brief explanation of GDW:

As with the previous metric, GDW had to be altered to fit the model of a Major League Baseball organization, and once again WAR is used in place of dollars. GDW is used to evaluate the transactions teams make each year. Unlike eWAR we will leave out the WAR for returning core players in order to isolate player transactions. This will allow us to compare the performance of players the team acquired versus the players they let go or traded. (Note: This excludes prospects projected performances that have yet to see action in “the show”. See note at the end of this piece.)

The formula for GDW:

GDW = WARcallups + (WARimports – WARexports)

The call-ups consist of any player(s) moved up from their affiliated farm system to the big league club. For example, Carlos Correa was a rookie in 2015 and contributed 4.1 WAR to the Astros “WAR call-ups” total that year. We used WAR of exported players in our calculation of eWAR, but just to remind you, WAR of players exported from the team is derived by looking at how well each player performed that year for their new team. WAR of imported players comes from those players who are new to the team, but were not call-ups from the team’s farm system. These are players who were acquired via trade or free agency.

The Astros come out on top of this list as well and once again this is not a huge surprise. The Astros received solid production from newcomers (imports) like Carlos Correa, Colby Rasmus, and Luis Valbuena along with many others. As mentioned before, only three of the players they got rid of actually had a positive WAR for their new club in 2015, meaning in general, they got rid of and brought in the right guys.

If you remember, I mentioned before that there were a couple of teams who made the postseason, but did not rank high on the eWAR chart. It turns out that the same teams also fared poorly with regards to GDW. The two teams that jump out are the Los Angeles Dodgers, who rank 18^th on the GDW list, and the Pittsburgh Pirates, who ranked 21^st. What does this mean?

For the Pirates, it could mean they relied more heavily on their returning players to provide production. Remember, I am not trying to see which team achieved the highest total WAR. I am looking at how well each front office managed player transactions (call-ups or new acquisitions). Being low on these two lists is not necessarily a bad thing. Conceivably, if a team returned every single player it had the previous year and never brought up any rookies, their GDW would be zero. This was the Pirates situation, to a degree, in 2015. Sure, Happ, Burnett, Kang and others added a great deal of value to the Pirates this season, but their core group still provided a majority of the production. For proof we can look at the percentage of total team WAR that was created by the Pittsburgh imports.

There’s our answer. The Pirates newcomers only contributed to 27% of the team’s total WAR. They were successful in large part because of their returning players. However, this is not to say those new guys didn’t play a big role in their success, just that Huntington and company thought they could get by with what their current team could provide them.

All that being said, as far as this season’s front office moves, GDW shows that the Pirates were not that great. I realize some of the moves had to do with salary issues, proving once again this system is not perfect, but from an economic standpoint the Pirates didn’t get any better from the moves they made with regards to current production. The wins above replacement added by their imports was 11.3, and the wins created by their exports was 11.1. I haven’t dug into the contracts, but hopefully Pittsburgh was attempting to generate a cost advantage. This would validate their reason for basically breaking even in the player transaction market this season.

The other team ambiguously low on this list was the Los Angeles Dodgers. Their 2.5 GDW placed them 18^th out of the thirty teams. Like Pittsburgh, the Dodgers imports did not contribute a great deal to the total team WAR (18%), but I believe this is only part of the explanation as to why they are so low on this list. I think another reason might be that Dodgers anticipated that their newly acquired talent would provide more fire power than they did. I think they also thought that the guys they let go or traded weren’t going to put up the numbers that they ultimately put up with their new clubs.

Before the season began, I used Steamer player projections to calculate the projected GDW of each team. At that time, Steamer along with GDW was bullish on the Dodgers’ off-season moves. In fact, if you review that old post you can see that they were ranked 6^th in the pre-season evaluations with a projected GDW of 5.4. Now take a look at the chart below. Use it to see which teams came close to matching their projections and which ones were off.

As you can see, Los Angeles’ projections fell into the latter category. They were off by -2.9 and the projections didn’t even factor in players who were acquired during the season. My point is that the Dodgers had to rely more heavily on their returning players out of necessity. The players they acquired and brought up did not live up to their expectations, assuming they used a system somewhat similar to Steamer to evaluate their acquisitions.

For the most part, I agree with these front office rankings from a subjective standpoint. As teams become increasingly dependent on player projections to help them find and acquire players, it is important that we try to grade those moves. That is what I have attempted to do here.

One downfall of using eWAR and GDW is that it does not take into consideration the future contribution of minor league players in each deal. That is a huge part of the game. I am currently working on a way to implement that into my grading and am optimistic I will have an update soon. In the meantime, hopefully the current version will provide a basis for discussion.