# This ShH Just Got Real!

Should Hit, or ShH — pronounced like: “Shh! Be quiet or the Nazis will hear!”

Last week, while rifling through the lump of cold numbers that is the 2011 season, I stumbled upon a self-illuminating chest of gold coins: A reliable, fielding independent hitting formula. Today, we’re going to take it to the next level and get nerdy up in this beach.

Before we proceed, let’s do some of the research I did not care to do the first time around. Here are some of Should Hits‘s predecessors (though they did not directly influence the creation of ShH):

FIP for Hitters
In 2010, Matt Klaassen wrote “FIP for Hitters? Defense Independent Offense.” His work in the article — though it does stay truly defensive independent and does not bring BABIP into the conversation — probably mirrors my work the most. However, his works is different both in process (he excludes BABIP and does not use wRC+) and intention (my tool focuses on regression, not really true talent levels).

Four Factors
In the middle of last year, Jack Moore got freaky with walks, strikeouts, a special ISO, BABIP, and home runs. Moore’s work also resembles my own in many ways. The key differences are: (1) the greater complexity of formula, (2) the inclusion of POWH (an ISO on hits only), and (3) Moore’s impressive display of algebraic prowess.

Ultimately, though, Moore’s work is not park nor league adjusted (a benefit ShH accrues through using wRC+), and it also is not defensive independent.

PrOPS
Someone mentioned “ProOPS” in the comments in my previous article and I was like: “Say what?!”

Well, PrOPS, spelled with one O, is a tool Hardball Times had been using for many an age. It’s an OPS predictor that uses a player’s batted ball data (line drives, groundballs, etc.), walk rates, strikeout rates, homer rates, and home ballparks to spit out the OPS his hitting profile suggests he should have.

Outside of being regression-based hitting-prediction tools, though, PrOPS and ShH have little in common. Where ShH is almost suspiciously simple, PrOPS is all-encompassing — and oddly less reliable (apparently a .81 R-squared, go figure).

Still each of these three metrics provide interesting insight and different angles of the same pursuit: understanding hitters.

Well, ShH just took it to the next level today.

Last week, many commenters — and myself — began to suspect ShH was systematically undervaluing speedy hitters, who hit more doubles and fewer homers. Because ShH has no doubles component or triples component (other than the unfairly weighted BABIP, which says both events equal 1), the Jose Reyes-types appeared to be getting a short shrift from ShH.

So, one of the suggestions was to include steals into the regression because steals aught to act as an acceptable (though not perfect) proxy for doubles and triples. Well, first, I wanted to see if this relationship really existed. It didn’t:

The hitters from 2009 through 2011 showed a weak — maybe even nonextant — relationship betwixt double/triples and steals.

Still, when we look at the top and bottom tiers of speed, we see there’s a problem. Looking at the best 37 thieves (i.e. those with 40 or more steals) from 2009 through 2011, we find that ShH undervalues them by an average of 2 points. Conversely, the 38 slowest lumberers (9 steals or less) were overvalued by 2 points.

As a whole, the two groups were still crazy close to their Should Hit predictions:

The “sluggers” (I put sluggers in quotes because this group included the likes of Yuniesky Betancourt) performed a little better, but not by much:

So, yeah, maybe ShH undervalues speed hitters? FIP — ShH’s mother — does the same thing with groundball pitchers and other specific types (thus: we need SIERA).

HOWEVER: Should Hit’s value is not in telling us a player’s present wRC+ — that’s what wRC+ does on its own. Should Hit allows us to adjust for a players BABIP — given his present peripherals. We are comparing the player internally, not externally.

In other words, we would not want to use Jose Reyes’s ShH to compare him to another player, but to compare him to himself with a different BABIP (or walk rate, strikeout rate, etc.).

To clarify this process, I created ShHAP!, a new Google Doc that should make everything clearer:

NOTE: You’ll need to save the Doc to your own Google Docs collection or download it as an Excel spreadsheet. Unfortunately, I can’t let just anybody edit it, or t’will likely be abused.

Using the same ShH formula as before, I have concocted the consummate Google Doc. Instead of having the Dying Ball Era-skewed wRC+ as before, this present rendition offers an internally adjusted formula:

Simply, ShHAP! takes the difference between a player’s career and current-BABIP-based ShH and applies that difference to the player’s present wRC+. Not simply, it looks like this:

Let’s look at Babe Ruth‘s 1923 season — a great season by any standards — wherein Ruth hit 226 wRC+ with a hefty .423 BABIP. Using his career BABIP, ShHAP! says he would have hit closer to his career norm — actually, worse.

Altogether, the ShHAP! formula narrowly follows Ruth’s career, indicating the changes in his performance mostly came from varying walk, strikeout, and homer rates — not from BABIP:

If we look at Lou Brock‘s career — the career of the prototypical high-speed, less homers guy — we see a similar trend:

Here we see ShHAP! predict Brock’s late-career resurgence as a low BABIP plagued his 1977 and ’78 seasons. Overall, ShHAP! keeps very close to Brock’s wRC+ — a good sign with regards to the speedy guy problem, especially seeing as how Brock had almost as many triples as he did homers.

So: Go! Play with ShHAP! and let me know what you think! Does it appear to still struggle with quick guys?

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Member
4 years 10 months ago

Can’t mess with the predictor ’cause it’s read/view only.

Guest
4 years 10 months ago

This is really cool. I wonder if one could make it (or a similar formula) work for a predictor for how minor leaguers could adjust to the majors when their BABIPs regress. Minor league player lines are frequently skewed by BABIPs that exceed .340, and I’ve always felt that is the biggest problem in looking at minor leaguers stats. Now, I’m sure it would be difficult to do, as changes in difficulty of competition would also effect peripherals, but if such a thing could work, it could be a very valuable tool.

Guest
4 years 10 months ago

Bradley, do you suppose this would be a predictive tool in the likely successful transition from minor league ball to the majors?

Guest
Justin
4 years 10 months ago

You should simplify that formula since most of those terms drop out.

Member
mattinm
4 years 10 months ago

Beat me to it. All ShHAP! is is BABIP vs xBABIP adjusted wRC+. Unless I’m misreading something somewhere.

Member
benjipants
4 years 10 months ago

Ok, so here’s the test for me: Michael Morse. I get an expected wRC+ of 143 compared to his 152 wRC+
Dude really doesn’t walk much, but he doesn’t strike out a ton, and he hits home runs. Assuming his career BABIP of .358 is remotely sustainable, he’s a damn fine player, but if it regresses to .300, he’s something like a 116 wRC+ player.

Here’s the question though–with such an extreme outlier like Morse in terms of BABIP, career arc, etc. do we really gain much predictive power here? He’s not exactly a TTO guy, but he’s not a speedy hitter’s hitter.

Member
4 years 10 months ago

My favorite thing so far is Bonds’ 2001 wRC actually goes up to 245. Is there a way to see career BABIP through a particular season? Just curious what it’d be with his career BABIP through 2001 rather than the latter end of his career.

Guest
Oscar
4 years 10 months ago

Okay, can you explain to me how this is any different than just normalizing a player’s batting average by using xBABIP or career BABIP instead of current BABIP and then recalculating their OPS (or wRC+ or whatever)? I can’t see a difference.

Member
4 years 10 months ago

Too much math x_x

Guest
Jason B
4 years 10 months ago

Or, in the form of a Head & Shoulders commercial:

Professor Woodrum: Is that too much math for your brain to comprehend, Joe?

Mauer: No!

Prof Woodrum (sternly): Is it?

Member
4 years 10 months ago

Hahah

Guest
Matt
4 years 10 months ago

Yes, but the real question is, are strike-outs bad?

Guest
4 years 10 months ago

to regress a hitter based on a different K%, BB%, HR%, or â€” most likely â€” BABIP.

Guest
ezb230
4 years 10 months ago

i asked this question of neyer/james in a chat years ago, and got shot down. yet to this day, i don’t get why FIP works for pitchers and not for hitters. if pitchers can’t control what happens after the ball leaves their hands, why do we assign credit/blame to hitters for what happens after the ball leaves their bats? either the pitchers get too little credit/blame or hitters get too much. anything else seems like a contradiction, imo.

Guest
Cliff
4 years 10 months ago

What does that even mean? Obviously there is no physical way for a pitcher to control the ball after it is out of his hand or for a hitter to control a ball after it is off his bat. But clearly what the pitcher does with the ball in his hand does effect where the ball ends up, and same with the hitter and his bat.

Guest
Will
4 years 10 months ago

“Obviously there is no physical way…for a hitter to control a ball after it is off his bat.”

That’s absolutely false. I once saw Carlton Fisk wave a home run fair.

Guest
Matt P
4 years 10 months ago

Pitchers do control what happens after the ball leaves their hands. That’s why monitoring strikeouts, walks and home runs makes sense. What they don’t control is what happens when a ball is put into play. Which is why penalizing a pitcher for having a high BABIP doesn’t make sense.

Pitchers usually pitch behind a set number of defensive players. Unless they’re traded, then their defense is going to be roughly the same for the whole season. Hitters hit against many different groups of fielders. So, it makes sense to say that fielding has a significant impact on how a pitcher performs but not on how a batter performs.

Member
holdenpi
4 years 1 month ago

another small simplification is ShHAP= wRC+ – 465*(BaBIP-xBaBIP)