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My previous column on reaching-base-via-error rates for batters
generated the most responses yet in the short life of this column, which I think
warrants a follow-up column responding to some of the reader mail on the
topic.

By far the most common point made by readers was that I neglected to
consider handedness when I presented the list of best and worst ROE%. T. M.
was the first to write in on this issue:


I noticed something about the reaching-on-error leaders and trailers. The
leaders are all either fast guys who make a lot of contact, which you might
expect, or right-handed power hitters, which you wouldn’t.

Among the "worsts," they are all left-handed pull hitters
except Chad Kreuter, who’s a switch-hitter.

It seems to me that the most important variable is hitting grounders to the
left side of the infield, where the throws are longer and small mistakes
lead to errors.


T.M.–and about a dozen other readers–were right on the mark, and it was
careless of me to miss this in my original analysis. In fact, right-handed
batters are 29% more likely than lefties–per plate appearance–to reach on
an error:


Batter ROE%, 1978-2000
Switch    Left     Right
1.12%    0.95%     1.23%


The next most common question is along the lines of what Cooper Nielson
wrote in to say:


I enjoyed the analysis of error rates. One thing I’d like to see included is
the batters’ groundball/flyball ratio. It stands to reason that players that
hit more ground balls would be the beneficiaries of more errors (you rarely
reach base because an outfielder drops a ball).


Intuitively, a propensity to hit ground balls does suggest a greater
likelihood of reaching by error. I took all batter seasons with 500+ PA from
1978-2000, and using the groundball and flyball data (where available, which
was not for all batted balls), broke the seasons into quartiles, and
calculated each quartile’s ROE%. Higher G/F ratios, which mean that batters
are hitting more ground balls, are associated with higher ROE%, as you can
see in the following table:


Batter ROE%, 1978-2000
Quartile      Min G/F     ROE%
Q1             0.31      0.95%
Q2             0.75      1.10%
Q3             0.92      1.16%
Q4             1.12      1.31%


A few readers thought that looking at plate appearances as the unit of
opportunity wasn’t the optimal choice. Dan McLaughlin writes:


[I]f you wanted to use ROE to measure differences in speed and hustle rather
than the impact of those differences, one thing to check would be to refine
the study to look at ROE as a percentage of balls in play (rather than plate
appearances overall), or better still–if the data were available–ROE as a
percentage of GROUND balls in play (there’s really not much ability in
reaching on a dropped fly ball). That might yield statistical evidence that
would shed light on similar "intangible" qualities that are even
harder to measure.


P.F. echoes Dan’s observation:


While the impact to OBP is probably best measured by the ratio of ROE to
plate appearances, wouldn’t the measure of this as a skill be best
calculated as the ratio of ROE to BIP (balls in play)? It seems like the
[list of] career leaders in ROE% is populated by a fair share of
hack-a-matics.


There are a couple of ways of looking at this. As Dan and P.F. (among
others) suggest, in order to reach base on an error you generally have to
the ball on the ground, or at the very least put the ball in play.
Eliminating the plate appearances in which that doesn’t happen yields a
"purer" measure of the ability to turn ROE opportunities into
actual ROE.

However, this isn’t sufficient if we want to know the magnitude of the
impact on the game as a whole, or in other words, the actual value of an ROE
ability. Only a fraction of plate appearances incur an ROE opportunity, and
that fraction systematically varies across players. ROE per ball in play (or
per ground ball) is a conditional probability, and we need the probability
of the condition itself to complete the sequence:

Prob{ROE in a plate appearance} = Prob {ROE given a ground ball} x Prob
{ground ball in a PA}

This is not to suggest that looking at ROE/GB or ROE/BiP is without merit.
Splitting the overall measure into component parts has some diagnostic
value. It may suggest a coaching strategy to encourage certain players to
hit more balls on the ground, if they are particularly good at inducing
errors (speedy right-handed batters seem to fit the bill, given our evidence
to date).

J.C. offers a few thoughts:


Wow, that low ROE list sure has a theme!

Of course, most errors of the base-reaching type should be made by the third
baseman and shortstop. Slugging lefty pull-hitters don’t have much truck
with those left-side infielders.

I’m guessing that Jack Clark grounded into a lot of double plays. It
would be interesting to compare ROE to DP…strong correlation might be
found. Perhaps strong enough to merit adjusting the DP factor in offensive
formulas?


Surprisingly, though the theory is sensible enough, we don’t see strong
relationships between hitting into double plays and reaching on errors. The
table below shows correlations between seasonal the frequency of double
plays and the rates of reaching via error (for the three ways of
conditioning ROE opportunities previously discussed). The DP/Opp column is
the rate of double plays per opportunity (defined as plate appearances with
a runner on first base and less than two outs).


           ROE%    ERR/BIP   ERR/GB     G/F    DP/Opp
ROE%                 0.966    0.856   0.262     0.040
ERR/BIP   0.966               0.909   0.185    -0.017
ERR/GB    0.856      0.909           -0.002    -0.056
G/F       0.262      0.185  -0.002              0.148
DP/Opp    0.040     -0.017  -0.056    0.148


Remember that correlations close to 1.0 imply a strong relationship between
the two measures (high values matching high values, and low matching low),
and those close to zero indicate no relationship. Negative correlations
indicate that the two measures move in opposite directions–if one goes
higher, the other tends to be lower.

David Marshall writes:


Just had to point out that the limitations on your data set (1978-2000)
probably caused some players to appear on the Low Career ROE% list whose
full careers might not have. If the prime years of a player’s career fall
before 1978, they won’t get any credit for their speed and hustle during
those seasons. Only their "old and slow" years are being analyzed,
but these stats are then labeled "career." So Carl
Yastrzemski
and Rusty Staub (for instance) are getting unfairly
downgraded, while in Darin Erstad‘s case, his ROE is an accurate
reflection of his batting and running style.


This is a fair assessment of the career data I presented, since it doesn’t
actually represent the full careers of some of the players listed.
Additionally, since some current players are still young and haven’t started
slowing down during their decline phase, they may look better at reaching
base now than they will at the conclusion of their careers.

B.K. writes:


Looking at your data on hitters who "create" the most errors and
least errors, I saw a very distinct pattern. The hitters who create the most
errors were overwhelmingly right-handed hitters (or switch-hitters) and the
ones who were the least likely to create errors were left-handed hitters.

If we think about the distribution of errors by position, I would be willing
to bet most errors occur at either shortstop or third base, particularly on
ground balls.


As we’ve seen earlier, right-handed hitters do reach via error more often
than lefties, so it makes sense that the left side of the infield produces
more of the errors. The longer throw to first base gives these positions
less time to recover from a bobble or hesitation.

Jeff Hauser thoughtfully muses:


It would seem as if "ROE" could [be subject to] enormous
"park effects"–the subjective borderline between what is a hit
and what is an error varies significantly between official scorers, and many
(all???) teams have regular or semi-regular scorers.


Well, that brings up an "unintended consequence" of inclusion of
ROE in OBP: if OBP was recognized as widely as it ought be, and ROE was
included, official scorers would be under less pressure from players to
grade errors on an artificially inflated/generous curve.

E.F. also suspect parks have something to do with it:


Interesting article about reaching base on errors. You might consider
looking at home stadium as well. Being a Braves fan in the ’80s I notice
that Bob Horner, Rafael Ramirez, and Mike Hubbard are
all in the career leaders. We all remember the shape of that infield at
Fulton County Stadium!!!


I may address this in a future column, but there have long been suspicions
that some official scorers in some parks are more generous than others in
charging errors. One reader suggested a hometown bias in charging errors
(home players getting fewer errors charged than visiting players).

I’m not sure what I would expect in this situation. Charging an error to a
visiting player means taking a hit away from a home player, and I’m not sure
that a hypothetically biased official scorer would be any more willing to
take a hit away from one of the team’s batters. It’ll remain a mystery, at
least for now.

Bob Evans writes:


I liked this, if only because I can’t remember the last time I heard about
Billy Sample or Ken Phelps.

I wonder if John Mayberry ever got frustrated that it never seemed to
happen to him? Just nine times? He might have had more grand slams! O.K.,
maybe not.

Maybe more reachable, I wonder what Mo Vaughn would say if you told
him of all active players, he’s the least likely to reach base because of an
error? Would he say, "You know, it always seemed to me like I never
catch a break like that," or would he say, "Do you know, I never
noticed?" Ask him next time you chat him up, would you?


I’ll ask Mo about that next time I visit the Foxy Lady. By the way, I show
no grand slams for Mayberry over the span of time.

And to close out this week’s column, here’s Chuck Nobriga, who puts the
whole topic in perspective for us:


Any good statistic showing Johnnie Disaster among the leaders can’t
be worth a damn.

Keith Woolner is an author of Baseball Prospectus. You can contact him by
clicking here.

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