Can a Really Great Glove Make Up for a Really Weak Bat?
Can guys like Rey Ordonez and Pookie really save enough runs with their glove to make them valuable?
Time and time again, you will hear someone say, “Rey Ordonez saves hundreds
of runs with his defense. It’s okay that he can’t hit.” Is that true? In one
sense, it is true that Ordonez saves hundreds of runs, but that is compared
to no one playing. Every shortstop saves hundreds of runs. Does Ordonez save
more runs than your average shortstop? And is the number of runs he prevents
as many as he costs the Mets at the plate by being such an anemic hitter?
Today’s sabermetric tools allow us to analyze baseball events in terms of run
values. I won’t pretend to understand the calculations behind VORP (www.stathead.com)
or EQA/EQR (www.baseballprospectus.com),
but I have a good grasp of Pete Palmer’s Linear Weights, Bill James’ Runs Created
and Jim Furtado’s Extrapolated Runs. You can take any batter’s hitting line
and convert it to run values.
Since Rey missed most of 2000, I’ll be using another defensive
whiz/weak bat player: Pokey Reese. Reese has reportedly been one of the hold-ups
in several trades for the Reds. Jim Bowden simply won’t part with Pokey. Is
Pokey worth it? Does his glove make up for his bat?
The work I’m about to perform isn’t new today. I
first looked at this in 1998, and developed a player rating system from it.
Like all player rating systems (yes, all), this is fallible and has weaknesses.
There are flaws in the systems I use, but none too severe to make the rating
system “bad”. My rating system is the only one that incorporates defense in
the player ratings. Also the run value accuracies aren’t pinpoint; they’re estimates.
They are good estimates, and the finite-ness is expressed because that’s what
the formulas yield. As a general rule (and this applies to all rating systems),
players that are close in run value can be described as equal. Try to set a
mental range of 5-8 runs when looking at a player’s numbers.
Offense can be calculated with a variety of systems. I use Jim Furtado’s Extrapolated
Runs. For a really in-depth explanation, see http://www.baseballstuff.com/btf/scholars/furtado/articles/IntroducingXR.htm.
xRuns - Extrapolated Runs:
= (.50 x 1B) + (.72 x 2B) + (1.04 x 3B) + (1.44 x HR) +
(.34 x (HP+TBB-IBB)) +(.25 x IBB)+ (.18 x SB) + (-.32 x CS) + (-.090 x (AB -
H - K)) + (-.098 x K)+ (-.37 x GIDP) + (.37 x SF) + (.04 x SH)
Here’s Pokey’s line from 2000:
If you care to do the math, that’s 70 xRuns. I prefer
to let Excel do my work.
Before we can really use those 70 xRuns we have to
account for the conditions under which they were generated. First, the runs
have to be park-adjusted. In 2000, Cinergy Field was a run-scoring haven, second
only to Coors Field in terms of park effect. This is unusual, as Riverfront
has largely been a neutral park (Park Factor, PF, of 100-102) for a long time.
For my system, I use the present season PF, averaged with the 3-year PF from
STATS, Inc. From 1997-99, Cinergy had a PF of 102. For 2000, the PF was 116.
This gives Cinergy a working PF of 105, and that is what we will adjust Pokey’s
xRuns with. This adjustment gives Pokey 67 xRunsp+.
We also have to adjust the xRuns total by the number
of chances Pokey had to generate them. As “outs” are baseball’s currency, I
use xRuns/out. Actually, for a season, I extrapolate to a full season’s worth of
outs. A full season’s worth of outs for an average player is 465 outs (about).
This number is not exact, but it is a good starting point, and I do judge all
players from the same baseline, which is the important part. Pokey only used
405 outs (518-132+3+3+5+8). This adjusts his xRuns upwards to 76 xRunsa+.
The average NL second baseman generated 102 xRuns in
465 outs; 104 excluding Pokey. Jeff Kent, the NL MVP, generated 153 xRunsa+. Edgardo
Alfonzo generated 149 xRunsa+. That means Pokey was 28 runs worse than the average
of the other regular NL second baseman at the plate. Can his glove be that valuable?
Note: Running these comparisons with Linear Weights
or Runs Created will result in almost identical numbers.
As I outlined in a previous article, http://www.baseballthinkfactory.org/articles/cdial_2001-03-06_0.shtml,
defense isn’t easy to quantify. Actually, it’s not so hard to quantify once
you have a system, but it is hard to convince skeptics that your system makes
sense and that it is a good estimator of defensive value. Some of you will be
convinced by the following paragraphs; some of you won’t.
STATS tracks all balls in play using Zone Ratings (ZR). For more on how ZR
is kept and works, see http://www.bigbadbaseball.com/glossary/zone.html.
I use ZR as the basis for my defensive rating system.
Taking the average number of balls per inning hit
into a fielder’s zone and multiplying by the average number of innings in a
season, I get a number that represents the number of plays a fielder would get
(at an average rate) if he played every inning of every game. This serves to
normalize the number of chances a player would get and yields a theoretical
number of runs a player might save/prevent.
Here’s what that means: A defensive game (DG) is
8.75 innings (not quite 9). 8.75 innings times 162 games is 1418 innings. In
2000, Pokey Reese played 1129 innings, or 129 DG. He had 405 ground ball chances.
That’s an average of 3.14 chances per DG. The NL average for chances was 3.05.
A full season at 2B with an average number of chances would get Pokey 494 chances.
Pokey’s ZR was 0.874. Had Pokey gotten 494 chances, he would have converted
432 of them. In comparison, NL MVP Jeff Kent had a ZR of 0.796. Kent would have
converted 393 of those 494 chances. In equal chances, Reese would get 39 more
outs than Kent. Well, what does 39 plays mean in runs?
I think this converts to runs readily, and almost
obviously: any play not made results in a baserunner. Each out has a value:
if it takes away a single, that’s worth 0.47 (hit) + 0.28 (out). Each subsequent
base is worth 0.31 runs (per Linear Wts). Here:
SS/2B: (0.987*plays made*0.75) + (0.013*pm*1.06)
That formula says that 98.7% of balls hit through
the SS/2B zones are singles (when not outs), and 1.3% are doubles. There aren’t
enough triples or home runs to count. These percentages were arrived at through
analysis of actual balls hit through these zones.
So Reese would save 326 runs (see, hundreds!). Kent
would save 297 runs. Reese would save 29 runs (RS) more than Kent. The average
NL second baseman would save 310 runs.
Looking at offense and defense together:
Player xRuns RS Total
Reese 77 326 403
Kent 153 297 450
Avg 2B 102 310 412
So a full season for both players would have Kent
being worth 47 more runs than Pokey. Studies say that every 10-11 runs is worth
a team win. That means Kent was worth 4 more wins than Pokey.
That’s not really fair to Pokey. Kent was the best
overall second baseman in the NL in 2000. How does Pokey compare to the average
second baseman? That will tell you if he is worth hanging on to. He was 9 runs
below the average second baseman. That is pretty close. The error in my metric
only allows me to say he was slightly below average. The value of 9 has some
imprecision to it. It could be 5 runs worse; it could be 15 runs worse. Before
you start asking about an average player versus a replacement player, I have
little choice but to use average for defense. As long as I am comparing these
players to each other, the baseline doesn’t particularly matter.
The answer is, no, Pokey’s glove does not make up
for his bat. Is it close? Yes, and I believe this same exercise for 1999 actually
will have Reese above average overall. Is he a superstar? No. He just doesn’t
hit enough. You can also see how much a good hitting player can be well above
average even with some defensive deficiencies.
For more on my methodology, see http://www.baseballstuff.com/fraser/articles/dpi.html.
Posted: June 04, 2001 at 05:00 AM | 8 comment(s)
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