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Minor League Equivalencies for Royals minor leaguers

How will they translate to the majors?

Minda Haas Kuhlmann

During this excruciatingly slow time of the baseball calendar year, people who have a passion for numbers and baseball, like me, sit down and evaluate occurrences from the previous season. So with all this boredom due to the lack of transactions this offseason thus far, I decided to compose my own Minor League Equivalencies (MLEs). For those of you that have no idea what I’m blabbing on about, the concept of an MLE was composed by the one and only Bill James. The purpose of MLEs are to equate performance in the minor leagues (or any league outside of Minor League Baseball for that matter) to the major leagues. For further reading, Dan Szymborski came out with an in-depth piece on MLEs years ago at Baseball Think Factory.

One thing to remember is that MLEs are not a prediction of what the player will do, just a translation of what the major league equivalence of what the player actually did is. This is useful for predictions however, because like, major league statistics, MLEs have strong predictive value. As strong as major league statistics (which was the goal of this). Bill James stated that MLEs were the most important concept that he had ever come up with.

Because I was so fascinated with these, I decided to dive in deeper. After some research and number crunching, I came up with my own MLE formula. I used a lot of the steps shown in the Szymborski piece linked above, but I also added in some factors and made some adjustments with research of my own.

Before I get into what I came up with for Royals minor leaguers, I’ll go over three of the important factors that go into these formulas.

Minor League Park Factors

As I went over in a previous post, it is very important to look at minor league numbers with context.

Evaluating players in the major leagues tends to usually be easier than evaluating players in the minor leagues. This is because in the majors, we have less factors to focus on. Mainly league factors. In the majors, we have two league factors (we’ll use ERA for this), the American League at 4.37 and the National League at 4.34.

This becomes way more extreme in the minors. You’ll have a league that favors hitters strongly, such as the Pioneer League (Rookie) with a league wide ERA of 5.65. Then a league that favors pitchers like the Southern League (AA) with an ERA of 3.60. That’s quite a difference.

In that article, I used ERA to show the extreme variety of run environments in the minor leagues. But in my MLE formula, I use park factors to measure offense on a ballpark basis. This helps even out hitters who may have played in a hitter-friendly or pitcher-friendly ballparks. All these numbers are easily retrievable from Baseball America.

Here are the numbers for Royals Minor League ballparks (Note that below 100 is below-average and above 100 is above-average).

Minor League Park Factors

Team Level Runs HR BABIP
Team Level Runs HR BABIP
Omaha AAA 107 146 100
Northwest Arkansas AA 103 86 107
Wilmington A+ 103 97 104
Lexington A 104 153 96
Idaho Falls Rookie 121 82 110
Burlington Rookie 94 124 94
  • We see that Werner Park (Omaha) plays to the home run big time, coming in at 46% above-average, highest mark in the Pacific Coast League.
  • Also favoring the long-ball a lot is Whitaker Bank Ballpark (Lexington), playing home runs at 53% above-average.
  • Like most of its Pioneer League counterparts, Idaho Falls is a very extreme run environment, as runs are scored at 21% above league average at Melaleuca Field.

Major League Park Factors

So after all the stats are adjusted for ballpark environments, we adjust them to fit the run environment at Kauffman Stadium... which as we all know, does not favor hitters. The park factors back this up, as Kauffman Stadium ranks lowly in the following categories.

  • 22nd in runs
  • 27th in home runs
  • 20th in hits

But it does play above-average in non-home run extra-base hits.

  • 11th in doubles
  • 8th in triples

But all-in-all, after we factor in the Kauffman Stadium park factors, a hitter’s offensive production will be suppressed to some extent.

League Factors

Factoring the strength of competition a player faced is probably the most interesting and most important part of this whole formula. This is done by grabbing these handy-dandy league translation numbers from Clay Davenport, provided here, and mixing them into our big formula. Here are the league factors for the affiliates of the Royals.

League Factors

League Level Royals Affiliate League Translation
League Level Royals Affiliate League Translation
Pacific Coast AAA Omaha 0.759
Texas AA Northwest Arkansas 0.667
Carolina A+ Wilmington 0.556
South Atlantic A Lexington 0.476
Pioneer Rookie Idaho Falls 0.387
Appalachian Rookie Burlington 0.381

All numbers courtesy of

Now these numbers might be confusing to some of you. But it’s fairly easy to understand with some explaining. For example, the number marked on the Pacific Coast League is 0.759. This means that one run in the PCL is valued at about 34 of a run at the major league level. Going on the further, the Texas League has a league translation number of 0.667, meaning a run there is worth about 23 a run up in the major leagues.

The Results

Looking at these following results might put a bad taste in your mouth, as there is not even one hitter in the whole system with an even remotely positive MLE.

Disclaimer: I cannot stress enough how these are not projections. These are simply just translations for how a hitter’s season would fare at the major league level. Although, these can be useful for projections, as it a good tool for projecting performance of a minor leaguer with little to none experience in the majors.

AAA - Omaha Storm Chasers

These are where the useful MLEs are, with AAA hitters being on the brink of the major leagues. Sadly though, the best hitter was Raul Mondesi at a .220/.233/.348 line. As you can see, Frank Schwindel did not grade out well, with his .321/.340/.528 line in AAA translating to a .221/.233/.329 line in the majors. This can be attributed to a lack of ideal peripherals and age.

AA - Northwest Arkansas Naturals

MLEs can sometimes be useful in AA, but most of the time it’s just a waste of time making these calculations (but I still enjoy it). Like AAA, there are not really any positives coming out of these numbers. The best hitter is catcher Nick Dini, as his .310/.381/.380 line in AA equates to a major league line of .209/.266/.251.

A+ - Wilmington Blue Rocks

MLEs are basically useless once you get below AA (but like I said, I enjoy doing them). The best hitter here was Chase Vallot, with Nicky Lopez and Anderson Miller at a close second.

A - Lexington Legends

Emmanuel Rivera and Khalil Lee were the best hitters here, coming in at lines of .165/.199/.225 and .139/.196/.217, respectively.

Rookie - Idaho Falls Chukars and Burlington Royals

Once you get this low in the minor leagues, you’re looking at a run being worth about 13 a run at the major league level. So generally, expect about 23 of offensive production to be lost in an MLE formula.

These numbers definitely aren’t a tell-all. A lot of hitters will over-perform their MLEs, a lot will under-perform. Nonetheless, these formula are lots of fun to play around with and are always a serviceable tool for projecting future performance in the major leagues.