Analyzing Hitters Jumping from AAA to the Majors

Over the last two seasons, several highly-touted rookies have struggled with the jump to the majors like Jo Adell, Jarred Kelenic, Joey Bart, and Josh Lowe. I examined strikeout and shift numbers. Also, I wanted to find the major league replacement level OPS where hitters get demoted this season. Usually, it’s just under .650 but I was wondering if it has changed.

I’m not going to put a story around each study. Examples of hitters struggling with the jump to the majors are everywhere. I just want the facts when those stories pop up in the future.

Strikeouts

I wanted to determine how much should a AAA hitter’s strikeout rate increase when making the jump from AAA to the majors. I just looked at hitters from 2021 and 2022 to see if the missed 2020 season would cause any issues.

The first test was to find the weighted mean of all the hitters (i.e those with more plate appearances have more of an influence). The weighted increase was a 4.7% point increase. Next, I found that the median increase was 4.4% points. for the general population, a 4.5% increase could be expected.

I wanted to take the analysis a bit further. Jarred Kelenic has a 28% K% in AAA but it has jumped to 38% in the majors. I was wondering if the 4.5% increase wasn’t linear but those who struggled in AAA just got owned in the majors. And the results were the opposite of what I expected.

AAA to MLB Hitter K%
AAA K% Weighted Average Median
<20% 6.1% 5.5%
20% to 30% 4.1% 4.0%
>30% 1.3% 1.4%

The high strikeout hitters see a bump but not as much as the low strikeout hitters. Kelenic must have been one of the exceptions.

The explanations for the movement on both sides are probably explained by regression to the mean. The low strike hitters would have seen their strikeout increase closer to the league average if they stayed in AAA. Also, the high strikeout hitters would have seen a drop.

The Shift

This study is again inspired by Jared Kelenic. So far this season, he’s been shifted on in all but one plate appearance. In 2021, His BABIP dropped from .323 in AAA to .216 in the majors. This season, the drop has been from .366 to .188.

I’ve tried within my power to find any minor league shift information. My thought was that hitters might not be shifted as much in the minors and when they get to the majors, certain hitters are affected more than others. Instead, I was forced to reverse engineer the major league shift numbers from the minor league rates. I ended up with mixed results.

The ease in which teams can shift lefties means that batter-handedness needs to be split up. I’ll start with those lefties.

Left-handed hitters

I used our major league shift rates and compared them to our minor league stats. I used ISO as a proxy for power and tried several groupings and here is the best one I could find.

Median AAA Batted Ball Stats Compared MLB Shift Numbers
Shift Weighted BABIP BABIP Pull% GB% FB% ISO Spd
<60% -.059 -.046 41.8% 47.1% 32% .157 5.0
60% to 75% -.030 -.035 42.8% 44.9% 34% .180 4.9
75% to 90% -.028 -.047 40.7% 41.6% 35% .191 3.5
>90% -.064 -.062 40.6% 39.1% 39% .234 2.6

There are definitely some traits for the hitters getting shifted and their BABIP is taking more of a hit. The key is finding hitters in the >90% shifted group. I sort of average three rates, GB% (<40%), ISO (>.200), and Spd (<3.0), from the two highest shifted groups. When I group by the number of these criteria met, here are the results.

AAA Criteria to Predict MLB Shift Rates
Criteria Met Median Shift% BABIP Drop
0 67% -.044
1 75% -.043
2 85% -.041
3 92% -.062
LHH: 2021 to 2022

Those rates are fine for the seasons in question. Here are the same criteria used for 2018 to 2019.

AAA Criteria to Predict MLB Shift Rates
Criteria Met Median Shift% BABIP Drop
0 38% -.041
1 57% -.057
2 76% -.063
3 81% -.031
LHH: 2018 and 2019

The three criteria work great for finding hitters who will be shifted, but the effects of the shift are a little up in the air for these lefties.

Right-handed hitters

Since righties are shifted at a lower rate, the breakpoints had to be adjusted.

Median AAA Batted Ball Stats Compared MLB Shift Numbers
Shift Weighted BABIP Median BABIP Pull% GB% FB% ISO Spd
0% to 25% -.030 -.042 43.6% 45.5% 33.9% .141 4.2
25% to 50% -.044 -.048 45.9% 40.2% 37.3% .181 3.4
>50% -.031 -.043 46.2% 38.2% 38.2% .179 2.6

The 40% GB% and 3.0 Speed Score lineup almost perfectly, but instead of the ISO value, a 46% Pull% was used instead for the three criteria. Here are the results depending on the three criteria.

AAA Criteria to Predict MLB Shift Rates
Criteria Met Median Shift% BABIP Drop
0 37.6% -.055
1 45.7% -.043
2 46.6% -.029
3 53.5% -.023
RHH: 2021 to 2022

The BABIP numbers don’t make sense on the surface. I guess hitters who spray the ball around get hurt by MLB defenders getting to more batted balls. Maybe. I’m still trying to digest this finding.

Now, moving on to back-test the data to 2018 and 2019.

AAA Criteria to Predict MLB Shift Rates
Criteria Met Median Shift% BABIP Drop
0 15.7% -.055
1 20.6% -.044
2 26.1% -.040
3 25.9% -.004
RHH: 2018 to 2019

The hitters who are shifted get pointed out, but the same BABIP trends perplex me.

Replacement level hitters

For this final study, I’m looking into MLB OPS for hitters who have bounced around to and from the majors. Basically, how bad does a batter need to be to get demoted. I set the minimum plate appearance total for each level at 85. I was hoping for 20 to 30 hitters.

OPS Values for Hitters in AAA & MLB
Name MLB PA AAA PA MLB OPS
Nomar Mazara 86 152 .742
Paul DeJong 86 179 .417
Luis Rengifo 169 112 .684
Travis Demeritte 96 101 .597
Luis Garcia 122 193 .790
Isaac Paredes 142 113 .907
Jo Adell 87 157 .693
Tyler Nevin 149 106 .560
Luis Barrera 85 150 .632
Matt Vierling 115 95 .708
Alex Kirilloff 95 157 .621
Jarred Kelenic 96 166 .509
Josh Lowe 117 157 .509
Seth Beer 93 183 .585
Richie Palacios 86 95 .634
Juan Yepez 193 93 .844
Jake McCarthy 86 151 .687
CJ Abrams 108 151 .543
T.J. Friedl 100 133 .539
Alek Thomas 187 116 .737
Calvin Mitchell 88 160 .553
Oscar Gonzalez 130 182 .746
Jose Miranda 164 95 .678
MJ Melendez 204 91 .727
Nolan Gorman 141 147 .783
Average= .657
Median= .678
Min 85 PA at each level

For now, this season’s numbers are in line with the historic values. Maybe just a bit higher.





Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR once, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

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nrbg27member
1 month ago

Spell it out for us dummies — what does this mean for the recent wave of callups? Who more/less likely to succeed?

Pat Gmember
1 month ago
Reply to  nrbg27

The man did the fishing for you and you’re asking for tartar sauce. 1. Take the first chart and add it to the MILB K% of a callup to approximate how much they’ll strike out in MLB. 2. Hitters who get shifted a lot (LH especially) will struggle more in MLB. Guys with a < .650ish OPS remain likely to lose MLB jobs.

nrbg27member
1 month ago
Reply to  Pat G

People commonly eat fish with tartar sauce.

Crazyhurdlersmember
1 month ago
Reply to  nrbg27

I agree. Two more paragraphs with “Players to Target” and “Players to Avoid” completes these type of articles.