Minors to the Majors: Hitter Metric Correlations

On Tuesday, I published the results of my research calculating correlations for various pitching metrics as pitchers transition from the minors to the Majors. Today, we’ll look at the hitters. Just like for pitchers making the jump from the minors to the Majors, hitter correlations are very similar to what Matt Klaassen calculated for MLB batters year-over-year. That may be a surprise, but it does mostly suggest that there’s not as much development from the minors to the Majors as we might expect. A baseball player is who he is, for the most part, on average. Now let’s get to the details.

I filtered for all hitters with at least 300 career minor league plate appearances and 300 career MLB plate appearances since 2006. My total player population equaled 853.

Minors to Majors: Batted Ball Type Correlations
LD% GB% FB% IFFB%
0.20 0.74 0.77 0.62

Similarly to pitchers, ground ball and fly ball rates are innate hitter skills that translate well to the Majors. That means that whether looking at a hitter or a pitcher, you can feel fairly confident that the rates posted in the minors is who he is as a player and will be in the Majors. However, both line drive and pop-up rate correlate much more strongly for hitters than pitchers. Though LD% doesn’t strongly correlate, it does correlate much better than for pitchers, suggesting that it’s mostly a swing plane thing and outside the pitcher’s control. This is further supported by an IFFB% correlation nearly double that by pitchers. It’s the hitter, with his uppercut swing, that generally determines whether the ball in play will be popped up.

This means that you should remain cautious with minor league hitters who have posted high IFFB% marks. It could lead to a disappointing BABIP and I don’t believe any of the projection systems account for this.

Minors to Majors: Batted Ball Direction Correlations
Pull% Cent% Oppo%
0.66 0.06 0.60

These correlations are similar to pitchers, but also a bit stronger. Generally, a pull hitter remains a pull hitter and vice versa. A hitter would have to consciously change his plate approach and swing mechanics to change his batted ball direction distribution. Even if the change is made, he has to hope it improves his offensive performance, or he might revert right back to what he had been.

Minors to Majors: Pitch Outcome Correlations
BB% K% SwStr%
0.72 0.82 0.71

High correlations across the board here, which isn’t too surprising. If you display strong plate patience in the minors en route to double digit walk rates, you’re likely to post higher walk rates in the Majors. If you swing at everything and/or make elite contact that allows you to put the ball in play before ball four, that’s likely to continue in the Majors. Obviously hitters improve their plate metrics all the time, and regress, but in aggregate, the minors results are your biggest clues as to what to expect from the hitter in the Majors.

Minors to Majors: Skill Metric Correlations
BABIP HR/FB SBA%
0.48 0.69 0.82

Notice how the first two metrics were labeled as “Luck Metrics” in the pitcher correlations post, while I named this “Skill Metrics”. Also recall that for pitchers, BABIP correlated at just 0.14 and HR/FB rate at a measly 0.02. The hitter correlations are significantly higher and confirm that this is a real skill. I’ve always said in my articles that BABIP does seem to correlate pretty well from the minors to the Majors, though to lower marks (for example, a .390 minor league BABIP might translate to a .350 MLB one). I never had the data to back up my observations while doing hundreds of player projections each year. Now I have confirmation. Pay attention to minor league BABIP, and even better, combine it with batted ball type distribution to ensure it makes sense. A fly ball guy popping up on 20% of his flies is highly unlikely to maintain a .350 BABIP, if that’s what he’s done in the minors. Remember, there’s still a whole heaping of luck involved in the minors, and even more so given the weaker defense.

Look at HR/FB rate! That’s quite high. We typically think of minor leaguers slowly developing power and perhaps eventually enjoying a spike after a couple of seasons in the Majors. This certainly happens, and quite often, but such a high correlation here suggests that in aggregate, hitters who haven’t displayed double digit HR/FB rates in the minors likely won’t in the Majors, and those who do, will probably do so in the Majors as well. That’s why I will always remain skeptical of guys who make their debuts and post HR/FB rates well above their historical minor league marks. It could be a real power breakout, but more than likely, it’s just a hot streak fluke.

Last, I added a new metric, SBA%, which stands for stolen base attempt percentage and is simply stolen base attempts divided by plate appearances. That’s a darn high correlation, as it should be! If you’re fast, you’re fast, and hitters generally don’t suddenly become major basestealers in the Majors when they weren’t in the minors, or stop stealing bases in the Majors after swiping so many in the minors.

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

Minors to Majors: Correlation Summary
Metric Correlation
K% 0.82
SBA% 0.82
FB% 0.77
GB% 0.74
BB% 0.72
SwStr% 0.71
HR/FB 0.69
Pull% 0.66
IFFB% 0.62
Oppo% 0.60
BABIP 0.48
LD% 0.20
Cent% 0.06

Nearly every metric discussed correlates rather well from the minors to the Majors. Obviously, league and park effects, in addition to age, level, etc, must be considered when evaluating minor leaguers. But if you simply want to get an idea if the latest call-up is worthy of a pick-up, ignore the scouting reports. Seriously. The minor league skill metrics should be more than enough to give you an idea of what you might get for the remainder of the season. Scouting reports might help for future potential, but if all you care about is the current year, stick with the minor league stats, as they tell you more than you may realize.

We hoped you liked reading Minors to the Majors: Hitter 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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baltic wolf
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baltic wolf

Nice column, Mike.
I’ve been busy with family problems lately, so I don’t have time to use your data at this time.
What do you think about Jake Cronenworth of Tampa Bay?
Thanks anyway if you don’t have time also. I always enjoy your deep analysis of players.