Don’t try to strike everybody out. Strikeouts are boring. Besides
that, they’re fascist. Throw some ground balls — it’s more democratic. — Crash Davis,
Bull Durham
On May 7 of this year, ChienMing Wang started for the Yankees against the Rangers
in a game played in Arlington. In typical fashion, Wang got three
groundball outs in the first inning and went on to beat the Rangers, 85. Wang ended up with the following line:
IP H R ER BB SO HR 6 7 3 3 0 2 0
Of his 16 outs on batted balls, 10 came on grounders, a typical number
for this groundball pitcher. The two strikeouts in six innings pitched was also
typical for Wang &mdash in fact, his groundball tendencies and low strikeout rate are Wang’s
two defining characteristics. Wang made what seemed like a slew of starts just
like this one: May 12 against Oakland: 8 IP, 0 runs, 0 K, win; May 27
against KC: 7 IP, 4 runs, 3 K, win; July 8 versus Tampa Bay: 8.1 IP, 1
run, 2 K, win; July 17 against the Mariners: 7 IP, 2 runs, 1 K, win;
and on and on and on. Pitching six or seven innings, a fair number of hits allowed, few
walks, very few strikeouts, even fewer home runs: ground balls and
wins — that was Wang’s MO in 2006.
Wang ended up as the most reliable pitcher on the Yankees staff this
year. I guess Mussina had stats that were just as good, but by the end
of the season, Wang was clearly the Yankees’ number one starter. You
will recall it was Wang that started Game 1 of the ALDS against the
Tigers (the only game the Yanks won, as it turned out). ChienMing
ended up the season with a record of 196 and an ERA of 3.63 in 218
innings pitched. The ERA was good enough for eighth in the American
League and he tied for the lead, with Johan Santana, in wins. However,
he struck only 76 batters, or 169 fewer than Santana. He was the only
pitcher in the top 10 ERA finishers to strike out fewer than 100
batters. Basically, it’s very, very hard to lead the league in wins
and strike out so few batters.
A Junk Stat: Strikeouts Per Win
I think I came across this stat the first (and only) time in a Rob
Neyer article back in the late ’90s. It’s a junk stat: not useful for
much, except for having fun.
Wang’s 2006 ratio of 4 strikeouts per win is extremely low. In fact, in the
last 15 years or so, not a single starting pitcher has
recorded such a low K/W ratio (min 10 game started, 10 wins). Here are
the top ten lowK/highW seasons from 1990 to 2005:
Most Extreme Strikeout/Win Seasons Since 1990 +++++++++  Name  Year  Team  G  GS  WL  SO  K/Win  +++++++++  Rueter, Kirk  2003  SFN  27  27  105  41  4.10   Welch, Bob  1992  OAK  20  20  117  47  4.27   Doherty, John  1993  DET  32  31  1411  63  4.50   Gullickson, Bill  1991  DET  35  35  209  91  4.55   Gullickson, Bill  1992  DET  34  34  1413  64  4.57   Morgan, Mike  1999  TEX  34  25  1310  61  4.69   Welch, Bob  1990  OAK  35  35  276  127  4.70   Robinson, Ron  1990  ML4  22  22  125  57  4.75   Halama, John  2001  SEA  31  17  107  50  5.00   Tewksbury, Bob  1990  SLN  28  20  109  50  5.00  +++++++++
Note that a preponderance a these seasons is bunched up near the 1990
cutoff. That’s because strikeouts per plate appearance have been
growing steadily since about 1920. So, generally speaking, as you go further back in time, you
find more lowK pitchers. Wang’s 2006 would be at the top of
this table, of course.
The LowK Pitchers
When you look at Wang throw, he doesn’t appear to be a very
lowstrikeout kind of pitcher. He seems to have good “stuff”, throws
in the lownineties, but, in fact, he only strikes out a bit over 3 batters per
game. That’s the lowest
K/G rate of any qualifying pitcher in baseball
in 2006. The surprising thing is that Wang
was so successful despite the low strikeout rate.
It’s useful to compare Wang to other lowK pitchers from 2006; here
are the 10 qualifying pitchers with the lowest Krates:
Low Strikeout Pitchers of 2006 ++++++++  Pitcher  IP  SO  K/G  ERA  HR/G  GB%  ++++++++  Wang C  218  76  3.31  3.63  0.52  62.8   Silva C  180.1  70  3.38  5.95  1.84  43.6   Cook A  212.2  92  3.94  4.24  0.73  57.8   Redman M  167  76  4.03  5.71  1.01  44.4   Trachsel S  164.2  79  4.21  4.99  1.23  41.5   Byrd P  179  88  4.29  4.88  1.27  38.5   Marquis J  194.1  96  4.33  6.03  1.58  42.9   Buehrle M  204  98  4.39  4.99  1.61  44.2   Benson K  183  88  4.42  4.82  1.66  41.3   Pineiro J  165.2  87  4.53  6.37  1.20  47.5  ++++++++
If you exclude Wang, this group had a composite ERA of 5.23 and no
other pitcher on the list comes close to Wang’s 3.63. Of course,
looking at the last two columns in the above table, we get an idea of
why Wang is outpitching his lowK counterparts: he gives up many fewer
home runs, which in turn is a consquence of his high groundball
percentage.
So, everything seems to make sense: Wang strikes out very few batters,
but he compensates for it by being very stingy with the home run. I
didn’t mention it before, but his control is very good, too: his walk
rate was only 2.2 per game. Everything looks pretty good.
But some people see the low strikeout rate and worry. They worry because
studies have shown that pitchers with low strikeout rates generally
have shorter, less successful careers than pitchers with high
Krates. Bill James, in the New Historical Baseball Abstract, wrote a
lengthy article, entitled “Bird Thou Never Wert”, on the subject. The
title is a reference to Mark “The Bird” Fidrych,
who had a phenomenal
rookie year in 1976 (199, 2.34), despite striking out only 3.7
batters per game. Fidrych was struck by injuries after that season,
and did not reach 500 career innings pitched. James is saying that
Fidrych would likely not have had a long career even had he remained
healthy: the strikeout rate was just too low.
The Future of ChienMing Wang
So, what kind of career can we expect Wang to have? Well, one way of
answering this question, or at least thinking about the question, is
to look for similar players from baseball’s past and see how they
turned out. So that’s what I did.
I looked for primarily starting pitchers of the last 50 years or so
who 1) accumulated between 200 and 400 innings in their first two
years in the majors, and 2) had an
ERA+ between 100 and 135. Wang has logged about 330 IP with an
ERA+ of 117 in his first two years. I find 161 such pitchers and
for each of them, I
calculated their peripherals like K/9, HR/9 and the like. Actually,
since strikeout and home run rates vary quite bit over the period I’m
considering, I need to work with normalized stats. Normalized stats
are obtained by dividing the regular stat by the league average and
multiplying by 100. If the stat is supposed to be small (like ERA),
then we divide the stat into the league average. In this way, all
normalized stats have 100 as the average, anything above 100 is “better”
than average and anything below is “worse” than average. As an
example, a pitcher with a normalized Krate of 110 strikes out 10%
more batters than the average pitcher.
So, for each of the 161 pitchers, I calculate the normalized versions
of strikeouts per nine innings, which I call K/9+. I also calculate
the normalized home run and walk rates, HR/9+ and BB/9+, and the G/F
ratio (not normalized). The following table shows the 10 pitchers with
the lowest (normalized) strikeout rate, along with Wang’s number so
you can compare:
LowK Pitchers to be Compared to Wang ++++++++  Name  Years  IP  ERA+  K/9  K/9+  G/F  ++++++++  Wang, ChienMing  200506  334.3  117  3.31  52  1.78  ++++++++  Holt, Chris  199697  214.3  112  3.99  58  1.55   Lamp, Dennis  197778  253.7  112  3.02  58  1.91   Thurmond, Mark  198384  294.0  124  3.24  58  1.21   Cocanower, Jaime  198384  204.7  104  3.21  63  1.86   Ruhle, Vern  197475  223.0  104  3.11  63  1.17   Lemongello, Mark  197677  243.7  103  3.40  64  1.02   Bunker, Wally  196364  218.0  124  4.00  65  0.91   Dunne, Mike  198788  333.3  108  3.83  65  1.17   Straker, Les  198788  237.0  106  3.76  65  1.01   Grimsley, Ross  197172  359.0  100  3.66  66  0.75  ++++++++
Wang’s normalized strikeout rate is lower than any of these guys. I
don’t know about you, but I don’t find these “comps” very inspiring, perhaps because
I hardly know who any of them are. Well, Ross Grimsley was an All Star
and Bill James wrote about Wally Bunker in the essay on DIPS in the
New Historical Abstract, and a couple other names are vaguely
familar, but I hope for Wang’s sake that he doesn’t end up on the
career similarity lists of guys like Cocanower, Straker or Lemongello.
But, strikeouts, as we’ve already discussed, isn’t the whole story
when it comes to Wang. We should also be looking at home runs allowed
and perhaps groundball to flyball ratio and probably walk rate,
also. Instead of running a table for each of those categories, I’m
going to combine all of them to give one “similarity score”. Actually,
I call my score “chi2” (pronounced chisquare, rhymes with highchair)
and its value is small when two players are very similar. I used this
same technique when profiling
Jeff Francoeur some time ago. So, without further ado, here are
the 10 most similar pitchers to ChienMing Wang, based on their first
2 years of pitching:
Top 10 Most Similar Pitchers to ChienMing Wang ++++++++++  Name  Years  IP  ERA+  K/9+  BB/9+  HR/9+  G/F  chi2  ++++++++++  Wang, ChienMing  200506  334.1  117  52  120  196  1.78  n/a  ++++++++++  Fontenot, Ray  198384  266.7  109  75  113  233  1.86  3.43   Hibbard, Greg  198990  348.3  120  68  135  191  1.15  4.17   Holt, Chris  199697  214.3  112  58  129  136  1.55  4.18   Magrane, Joe  198788  335.7  134  92  107  199  1.83  4.58   Ruffin, Bruce  198687  351.0  115  69  113  148  2.07  4.61   Pichardo, Hipolito  199293  308.7  108  67  117  155  1.27  5.21   Hamilton, Joey  199495  313.0  134  81  135  139  1.47  5.56   Lawrence, Brian  200102  324.7  108  94  144  147  1.59  5.85   Reuschel, Rick  197273  366.0  131  114  147  175  1.66  7.59   Stieb, Dave  197980  372.0  111  85  102  152  1.35  7.71  ++++++++++
All but one of these guys (Reuschel) had belowaverage K rates, they
all had plus control and were all stingy with the home run. Each one
was also a groundball pitcher, for the most part. Of course, the
method was designed to find pitchers like this, so it’s no
surprise. So, who is this Ray Fontenot guy, the most Wanglike of the
pitchers in our sample? Actually, there are some curious parallels between
Fontenot and Wang.
At the age of 25 Fontenot was called up midseason by the Yankees
and made 15 starts; he won 8 games with an ERA+ of 118.
At the age of 25 Wang was called up midseason by the Yankees
and made 17 starts; he won 8 games with an ERA+ of 111.
Fontenot pitched his second full season
with the Yankees, as did Wang. Current fans of the Yankees will hope
the similarity ends there, because Fontenot spent his third season pitching for
the Cubs, going 610 and seeing his ERA+ drop to 92. Thereafter banished to the
bullpen, Fontenot pitched one more year and then was out of
baseball. Will Wang follow a similar career path?
Well, Fontenot’s just one guy, you can’t make any predictions based on
that. Let’s have a look at the careers of these 10 most Wanglike pitchers:
Career Results for Top 10 Wang Comparables +++++++  Name  IP  W  L  ERA+  chi2  +++++++  Fontenot, Ray  493.7  25  26  98  3.43   Hibbard, Greg  990.0  57  50  99  4.17   Holt, Chris  736.7  28  51  93  4.18   Magrane, Joe  1096.7  57  67  103  4.58   Ruffin, Bruce  1268.0  60  82  99  4.61   Pichardo, Hipolito  769.7  50  44  105  5.21   Hamilton, Joey  1340.7  74  73  94  5.56   Lawrence, Brian  934.0  49  61  95  5.85   Reuschel, Rick  3548.3  214  191  114  7.59   Stieb, Dave  2895.3  176  137  122  7.71  +++++++
Reuschel and Stieb are not really very similar to Wang: note the jump of almost two in
chi2 between the 8th and 9th pitchers. (Oops, I probably should have excluded Lawrence,
since he is still active.) Anyway, only the notverysimilar Stieb and Big Daddy
managed to win 100 games in their career. Of the first eight
listed, 6 of them ended up with below average career ERAs.
At this
point, I would normally proceed by taking a group of players that I deem similar to
Wang, look at their average career and compare them to the others, the
unWanglike pitchers. However, the answer you get when you do this is
going to depend on who you include in the list of Wang comps. You can
see from the table above, that the 9th and 10th pitchers on this list
are going to change the results quite a bit, depending on which group
you put them in.
Well, let’s just plunge ahead and see what happens. Let’s take all
10 of these guys and declare them similar to Wang. If we then look
at the average career of these the group of these 10 (I’m going to
call them the Wangers) and compare them
to the average career of all the others, this is what we find:
Average Career of Wangers vs. NonWangers, Top 10 Comps +++++++   Number  IP  ERA+  W  L  +++++++  like Wang  10  1407  102  79  78   unlike Wang  151  1266  102  75  68  +++++++
We see no real difference between the two groups, if anything the
Wangers have a slightly longer career on average. This would indicate that
Wang’s profile doesn’t really impact how long or successful his career
might be.
On the other hand, if you decide that Reuschel and Stieb shouldn’t be in the Wang
group, you get a different result: namely that the Wangers have shorter and less successful
careers than the nonWangers. Here are the numbers including eight
pitchers in the Wanglike group:
Average Career of Wangers vs. NonWangers, Top 8 Comps +++++++   Number  IP  ERA+  W  L  +++++++  like Wang  8  954  98  50  57   unlike Wang  153  1292  103  77  70  +++++++
So, the answer you get depends on where you draw the line. It’s not very satisfying, I admit, but that’s
the way it is.
The Other Extreme
Here are the 10 pitchers in the sample who were least like ChienMing Wang:
Ten Worst Comps for Wang ++++++++++  Name  Years  IP  ERA+  K/9+  BB/9+  HR/9+  G/F  chi2  ++++++++++  Eckersley, Dennis  197576  386.0  120  170  85  99  0.47  54.57   D'Acquisto, John  197374  242.7  102  141  66  107  0.57  43.67   Bibby, Jim  197273  236.7  100  142  63  104  0.73  41.88   Sanderson, Scott  197879  229.0  114  144  109  96  0.49  41.65   Lemaster, Denny  196263  323.7  111  124  90  69  0.61  41.20   Johnson, Bob  196970  215.7  123  153  101  120  0.59  39.31   Bere, Jason  199394  284.3  122  137  72  111  0.65  38.73   Smoltz, John  198889  272.0  103  117  91  83  0.51  38.34   Montefusco, John  197475  283.0  121  156  104  144  0.56  37.81   Benes, Andy  198990  259.0  105  124  93  88  0.55  37.80  ++++++++++
These were flyball pitchers who punched out a ton of batters, but also walked quite a few and gave
up there share of home runs. Interesting to see Eckersley at the top of the list: we remember him, of course, as the oneinning
relief specialist, he was quite the highoctane starting pitcher when he came up as a 20yearold in 1975. The career stats of these
UnWangs is quite a bit better than the Wangers:
Career Stats of UnWangLike Pitchers +++++++  Name  IP  W  L  ERA+  chi2  +++++++  Eckersley, Dennis  3285.7  197  171  116  54.57   D'Acquisto, John  779.7  34  51  80  43.67   Bibby, Jim  1722.7  111  101  99  41.88   Sanderson, Scott  2561.7  163  143  102  41.65   Lemaster, Denny  1787.7  90  105  96  41.20   Johnson, Bob  692.3  28  34  103  39.31   Bere, Jason  1111.0  71  65  86  38.73   Smoltz, John  2929.3  177  128  126  38.34   Montefusco, John  1652.3  90  83  103  37.81   Benes, Andy  2505.3  155  139  104  37.80  +++++++
Final Thoughts
As I mentioned in my article on Francoeur, I’m not totally convinced that the similarity method actually works. It might work,
but then again it might not. But it’s a fun analysis, it conjures up players from the past, maybe guys you haven’t thought about
in a while (like Big Daddy Reuschel). And perhaps it does tell us something about what we can expect from a guy like Wang going
forward. No, I can’t draw any firm conclusions from the numbers, but it seems to me that the cards are stacked eversoslightly against
Wang having a 100win career. Wait, let me clarify: the cards are stacked against any pitcher having a 100win career: only 42 of the 161
pitchers in our sample won 100 games or more. And these guys all looked promising after two seasons in the majors.
But, it looks to me that the odds are a bit worse for a guy
like Wang who strikes out so few batters. We’ll see, I guess.
References & Resources

I tend to be a believer in DIPS, so I did not include hit rates in
my comparison. I have tried doing so, though, and the basic results
don’t change. Only one player in the top 10 changes: Reuschel drops out and some guy named
Randy Tomlin takes his place.  G/F Ratio — my G/F ratio is slightly different than others you’ll come across. That is because full groundball/flyball
info is not available going back fifty years. So, I had to devise my own version using Retrosheet
data. It certainly is good enough for this analysis.  The details of the chi2 calculation were given in my article on Francoeur here. Of course, the batting statistics used there have been replaced by
the pitching statistics discussed above.