At the end of January, the author published a post here featuring roughly calculated WAR figures for every minor leaguer from 2014. Despite the conspicuously haphazard computation, the results of that effort were ultimately (and strangely) credible. The four players atop the relevant leaderboard from 2014, for example — Kris Bryant, Joey Gallo, Joc Pederson, and Corey Seager — are also the sort who will populate the upper regions of this spring’s top-prospect lists.

Over the course of a subsequent television appearance during which I (notably) cried zero times, I endeavored to explain why — even while batting leaderboards in the high minors, especially, are often crowded with the names of immobile, Quad-A sluggers — why minor-league WAR (or mWAR, for short) might favor actual prospects. One reason, it would appear, is this: while those older sluggers are typically relegated to first base or a corner-outfield spot, organizations will typically deploy their younger and more promising talents at the most challenging positions they can reasonably handle. As a result, those players benefit from a greater positional adjustment and, in turn, better mWAR figures.

Given the relative success of that first post, what I’ve attempted to provide here — made possible largely by my colleagues Jonah Pemstein and Jeff Zimmerman — is a leaderboard featuring the top-35 players by mWAR since 2006. Below that is a link to a spreadsheet containing mWAR figures for over 30-thousand player-seasons, also since 2006.

The methodology for calculating this version of mWAR bears considerable resemblance to the one I utilized in that original post. wRAA is batting runs relative to league (but not adjusted for park). BsR is base-running runs derived from Speed Score (or, Spd). Def, once again, denotes only a player’s positional adjustment and includes no attempt even to estimate something along the lines of runs saved.

Below is a (sortable) table featuring the top-35 seasons by mWAR since 2006. Below that is a collection of assorted observations. Note that Org and Age denote team and age from the relevant year. Levels denotes the number of minor-league levels at which the player recorded plate appearances in that particular season. mWAR600 denotes mWAR prorated to 600 plate appearances.

Some assorted observations and caveats:

• Including exactly the top-35 players by this measure might appear to be the product of some curiously arbitrary decision-making. There’s some logic behind the choice, however, as 35 is the minimum number required to include 18-year-old Mike Trout on the list while also rounding to the nearest -0 or -5. Trout recorded a substantial quantity of plate appearances in 2010 both at Class-A Cedar Rapids and High-A Rancho Cucamonga. He was among the youngest players in each league and also produced one of the top-50 minor-league seasons (or top 0.1%) over basically the last decade.

• Only one player produced two seasons which appear among the top 35: Adam Eaton in 2011 and -12. Eaton produced a .401 BABIP over the 1353 plate appearances he recorded between those two campaigns — undoubtedly aided by the run environments in both the California and then Pacific Coast Leagues. His batted-ball profile has carried over to the majors, however, too: in 900-plus plate appearances with the D-backs and White Sox, Eaton has posted a .333 BABIP. Both Steamer and ZiPS, meanwhile, project Eaton to produce the highest BABIP figure among all White Sox batters in 2015.

• In addition to having recorded the highest mWAR in 2014, Cubs third-base prospect Kris Bryant also appears to have produce the highest one since 2006 — i.e. all the years for which this data is available from FanGraphs.

• In the case of some journeymen-types or certain prospects who never established a true defensive home, the positional adjustment assessed to those players might not entirely reflect the number of innings said player logged at that position. This is a product of how the player’s position is classified in the site’s database. A brief examination of the results here suggests that this affects less than 10% of players. But it also serves to reinforce the notion that the mWAR figures here oughtn’t be regarded as infallible, but rather merely a tool for better understanding minor-league performances.

• Once again, Arizona Fall League numbers are included in the calculations for mWAR.

• A complete leaderboard of minor-league WAR is available in the form of an unkempt Excel worksheet by clicking here