Minors to the Majors: Pitcher Metric Correlations

Yesterday, I identified and discussed 11 starting pitchers significantly outperforming their SIERA marks, suggesting potentially major impending regression. One such pitcher on the list, ranking second in SIERA outperformance, was Mike Soroka. Through 10 starts and 65.1 innings, Soroka has allowed an amazing microscopic HR/FB rate of just 2.9%, which easily leads all qualified pitchers in baseball.

A commenter pointed out that Soroka’s minor league numbers suggest some ability to suppress home runs. Indeed, his performance down on the farm was quite magnificent, as he posted a minuscule 4.6% HR/FB rate throughout his minor league career spanning 370.2 innings. So because he displayed such home run suppression skills in the minors, and so far they have been maintained in the Majors, we can now confidently anoint Soroka as a HR/FB rate king, right? Not so fast.

In my response to the commenter, I began thusly:

Pretty confident that minor league HR/FB rate is meaningless.

Of course, I had no data or studies to link to backing up my assumption. When pressed for a justification of my confidence, I replied:

Sample size, wildly varied level of competition, significant ballpark effects, and what worked in the minors might not work in the Majors.

I hate to make assertions without the data to back it up. So as a result, I was inspired to expand my research to all pitcher metrics to see if I am right and what metrics, if any, correlate upon transitioning from the minors to the Majors.

I exported the career minor league stats of every pitcher since 2006 and removed those who recorded fewer than 50 innings. That left me with a whopping 8,733 total pitchers.

I then exported the career Major League stats of every pitcher since 2002 with a minimum of 50 innings pitched.

Last, I performed a VLOOKUP using the Player ID to pull the minor league stats worksheet over to the Major league stats worksheet. I then removed all players missing minor league stats.

Finally, my player population totaled 1,160, which is a reasonable sample size.

What follows are correlations and observations of most of the important metrics you care about from the minors to the Majors.

Minors to Majors: Batted Ball Type Correlations
LD% GB% FB% IFFB%
0.07 0.75 0.74 0.34

Not surprisingly, minor league line drive rate allowed is pretty meaningless. On the other hand, ground ball and fly ball rates mean a whole lot. Generally, a ground ball pitcher in the minors is going to remain one in the Majors, and vice versa. Pop-up rate is nowhere near as correlated, but still meaningful enough to suggest that pitchers do carry over some of those skills. Interestingly, these correlations almost perfectly match the Major League Year-to-Year correlations Matt Klaassen calculated back in 2013. Every metric in the above table has a slightly lower correlation than on Matt’s table, but the order is the same and the gaps similar.

Minors to Majors: Batted Ball Direction Correlations
Pull% Cent% Oppo%
0.56 -0.06 0.47

This surprises me. I would have never guessed the correlations for Pull% and Oppo% would be this high. Perhaps this is a proxy for pitch location or the pitcher’s pitch mix, both of which won’t change drastically in the Majors. It’s weird that Cent% is so low and actually negative!

Minors to Majors: Pitch Outcome Correlations
K% BB% SwStr% Str%
0.68 0.61 0.55 0.51

No surprises here as all four of these metrics carry over to some degree to the Majors. I find two things interesting here — the SwStk% correlation is meaningfully below K%, while Str% (strike percentage) is meaningfully below BB%. So both per pitch metrics are below the related plate appearance outcome metric. Odd.

Minors to Majors: Luck Metric Correlations
BABIP HR/FB
0.14 0.02

Finally, we get to the meat and the entire reason I did this research to begin with.

While BABIP’s correlation is quite low, it’s not completely meaningless. This does make sense, but it’s unlikely related to the pitcher’s skill or lack of skill in suppressing hits on balls in play. Instead, it’s probably more a function of the pitcher’s batted ball type profile, which as we learned above, carries over pretty well to the Majors.

Now, take a close look at that HR/FB rate correlation. Can you see it or shall I provide a magnifying glass? That correlation is essentially nada. There is absolutely no correlation between a pitcher’s minor league HR/FB rate and his Major League fly ball rate. This is exactly what Matt Klaassen found in his correlation calculations, though strangely, he found a negative number. Regardless of whether you look at the correlation of HR/FB rate from the minors to the Majors or the Majors Yr 1 to the Majors Yr 2, you will reach the same conclusion — if there is any skill difference between pitchers, it’s near impossible to capture and driven primarily by both luck and a myriad of other factors.

Now let’s summarize the metrics from highest to lowest correlation from the minors to the Majors.

Minors to Majors: Correlation Summary
Metric Correlation
GB% 0.75
FB% 0.74
K% 0.68
BB% 0.61
Pull% 0.56
SwStr% 0.55
Str% 0.51
Oppo% 0.47
IFFB% 0.34
BABIP 0.14
LD% 0.07
HR/FB 0.02
Cent% -0.06

This sorted list simply reiterates what we already know to focus on for Major Leaguers. If you’re evaluating a minor league pitcher, ignore his BABIP, LD%, and HR/FB rate. Focus on his batted ball profile (ground ball, fly ball, or neutral), his strikeout rate (and to a lesser extent SwStk%), and walk rate (and to a lesser extent Str%). That’s really it. Obviously, there’s no reason to concern yourself with ERA, although it might influence the organization’s decision on whether or not to promote the pitcher.

We hoped you liked reading Minors to the Majors: Pitcher Metric Correlations by Mike Podhorzer!

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Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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hebrew

this is awesome work for those of us in dynasty or keeper leagues! thanks, Pod.