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This week’s question comes from Chuck Hildebrandt, who writes:


Being a lifelong Detroit Tiger fan, I was studying the 1984 season in
Total Baseball when I was startled by something I saw in the National
League. I noticed that the New York Mets, managed by Davey Johnson, were
outscored by their competition, 652-676, yet finished the season with a
90-72 record.

This is a stunning display of overachievement, a team being outscored yet
finishing with a .556 winning percentage. Being too lazy to pursue the issue
myself, I ask the question of you: what are the greatest differentials, both
positive and negative, between expected and actual winning percentage for
any single team?

Bonus philosophical question: What do such differentials really say about a
manager's influence on a team, versus dumb luck?

Thanks for the question, Chuck.

First, let’s limit ourselves to teams that played at least 100 games in a
season, as some teams in the early days of professional baseball played
incomplete schedules. In order to find a team’s expected number of wins,
we’ll use the
Pythagenport formula–Clay
Davenport’s refinement of Bill
James’s original Pythagorean formula. The formula is:

Win% ~=  R^E/(R^E + RA^E) , where E = 1.5*Log((R+RA)/G) + 0.45

Given an estimated expected winning percentage, we can compute the
difference between a team’s actual and expected records either based on
winning percentage or difference in wins.

(To answer this question, I’m using the free downloadable statistics
database at
www.baseball1.com. The database
is currently unavailable due to server problems, but is expected to be
back online soon.)

Chuck, you have a keen eye. The 1984 Mets turned out to be the
second-biggest overachievers ever, at 11.7 wins above expectation, beaten
only by the 1905 Tigers, who went 79-74 while scoring 512 runs and allowing
602. They "should" have gone about 66-88, but instead managed to
be five games over .500, and 12.8 wins over expectation.

On the underachieving side, there are two teams that lost 13 or more games
beyond expectation. The worst underachievers were the 1993 Mets, whose 672
R/744 RA differential should have been good for a 73-89 record. They instead
posted a gruesome 59-103 record, or 14.3 wins below expectation. The other
unlucky team was the 1986 Pirates, who scored 663 runs and allowed 700,
which should have earned them a 77-85 record, but instead they went 64-98, a
13-game differential. The worst underachievers who actually outscored their
opponents were the 1907 Reds, who scored 526 runs and allowed 519. They
projected to a 79-77 record, but actually went 66-87.

Here’s a list of all teams with differentials of 10 or more games:

G500 = Games over .500
Pyth = Pythagenport expected winning percentage
P_W  = Pythagenport expected wins
P_L  = Pythagenport expected losses
DIF% = Difference between actual and expected winning percentage
DIFW = Difference between actual and expected wins


YEAR


TEA


LG


G


W


L


WIN%


G500


R


RA


PYTH


P_W


P_L


DIF%


DIFW


1993


NYN


NL


162


59


103


.364


-44


672


744


.453


73.3


88.7


-.089


-14.3


1986


PIT


NL


162


64


98


.395


-34


663


700


.475


77.0


85.0


-.080


-13.0


1907


CIN


NL


156


66


87


.431


-21


526


519


.506


78.9


77.1


-.074


-12.9


1905


DET


AL


154


79


74


.516


5


512


602


.430


66.2


87.8


.086


12.8


1911


PIT


NL


155


85


69


.552


16


744


557


.630


97.6


57.4


-.078


-12.6


1905


SLA


AL


156


54


99


.353


-45


511


608


.425


66.3


89.7


-.072


-12.3


1905


CHN


NL


155


92


61


.601


31


667


442


.671


104.0


51.0


-.070


-12.0


1975


HOU


NL


162


64


97


.398


-33


664


711


.469


75.9


86.1


-.071


-11.9


1984


PIT


NL


162


75


87


.463


-12


615


567


.535


86.7


75.3


-.072


-11.7


1984


NYN


NL


162


90


72


.556


18


652


676


.484


78.3


83.7


.072


11.7


1967


BAL


AL


161


76


85


.472


-9


654


592


.544


87.6


73.4


-.072


-11.6


1946


PHA


AL


155


49


105


.318


-56


529


680


.390


60.4


94.6


-.071


-11.4


1955


KC1


AL


155


63


91


.409


-28


638


911


.333


51.6


103.4


.076


11.4


1954


BRO


NL


154


92


62


.597


30


778


740


.524


80.7


73.3


.073


11.3


1937


CIN


NL


155


56


98


.364


-42


612


707


.434


67.2


87.8


-.070


-11.2


1917


PIT


NL


157


51


103


.331


-52


464


595


.396


62.2


94.8


-.065


-11.2


1970


CIN


NL


162


102


60


.630


42


775


681


.560


90.8


71.2


.069


11.2


1935


BSN


NL


153


38


115


.248


-77


575


852


.321


49.1


103.9


-.073


-11.1


1972


NYN


NL


156


83


73


.532


10


528


578


.461


71.9


84.1


.071


11.1


1924


SLN


NL


154


65


89


.422


-24


740


750


.494


76.0


78.0


-.071


-11.0


1890


CL6


AA


140


79


55


.590


24


831


617


.643


90.0


50.0


-.053


-11.0


1906


CLE


AL


157


89


64


.582


25


663


482


.636


99.8


57.2


-.054


-10.8


1919


WS1


AL


142


56


84


.400


-28


533


570


.470


66.8


75.2


-.070


-10.8


1924


BRO


NL


154


92


62


.597


30


717


675


.528


81.4


72.6


.069


10.6


1999


KCA


AL


161


64


97


.398


-33


856


921


.463


74.6


86.4


-.066


-10.6


1904


CLE


AL


154


86


65


.570


21


647


482


.626


96.4


57.6


-.056


-10.4


1993


SDN


NL


162


61


101


.377


-40


679


772


.440


71.3


90.7


-.063


-10.3


1911


CHA


AL


154


77


74


.510


3


719


624


.566


87.1


66.9


-.056


-10.1


1970


CHN


NL


162


84


78


.519


6


806


679


.580


94.0


68.0


-.062


-10.0


1932


PIT


NL


154


86


68


.558


18


701


711


.493


76.0


78.0


.065


10.0


1961


CIN


NL


154


93


61


.604


32


710


653


.539


83.0


71.0


.065


10.0

Of course, teams play 162 games today, versus 154 or fewer in years past, so
it’s a little easier to run up a larger differential over more games. If we
look just at differences in winning percentage, there are nine teams that
were 75 points or more off expectation. The ’93 Mets still top the list, at
89 points below expectation, but a new team, the 1981 Reds, turns out to be
the biggest overachiever, exceeding its expected winning percentage by 87
points (going 66-42, .611 versus a projection of 56.6-51.4, .524). Other
teams with 75+ point differentials but not a 10-game overall difference
include the 1884 Chicago White Stockings (later known as the Cubs) as
78-point underachievers, and the 1894 New York Giants as 76-point
underachievers.

Let’s consider Chuck’s second question: "What do such differentials
really say about a manager’s influence on a team, versus dumb luck?"
Strategic blunders by the manager can certainly influence a team’s record,
but the magnitude of this effect over the course of a season is hard to
estimate. A manager probably has a more important influence on his team in
playing the right lineup, managing the pitching staff, keeping his bench
fresh, and so on, than in specific game tactics.

A team that underachieves its projection as badly as the teams we’re talking
about probably lost more than its share of one-run games, which can be
caused in part by a lousy bullpen. The 1999 Royals, who are in the table
above, had a terrible bullpen, possibly one of the worst ever. When no one
is getting the other guys out, it’s hard to blame all of that on the
manager.

Of course, the arguments above aren’t very sabermetric. Let’s ask a slightly
different question: are teams who underachieve or overachieve likely to
continue doing so the next season? This doesn’t necessarily answer the
question about the manager’s impact, because a manager’s job is somewhat
more at risk following a season that didn’t meet expectations, but it’s a
place to start.

I took the list of all teams with 100+ games and compared their DIFW in one
season to the next (assuming the franchise still existed). I computed the
correlation of the two differentials. If the correlation was close to 1.0,
then teams were more likely to have the same kind of differential (above or
below average) the following season. If the correlation was close to -1.0,
the reverse is true, which would mean that teams that overachieve one year
are more likely to underachieve the next. A value close to zero means that
there’s no relationship between the two, that nothing from the team’s
"luck" carries over to the next season. The actual correlation was
+0.05, which is pretty close to zero, and suggests that there’s no
relationship.

We can refine the question a little bit more; since teams who overachieve
are more likely to retain their manager, we can focus only on teams that
were significant overachievers. I selected five or more games as a
threshold. Plotting their win differentials in the following season, we get
the following chart, which shows no real trend or pattern, furthering the
theory that the manager has little consistent impact on whether a team over-
or underachieves it’s expected Pythagenport projection.

* * * * *

A few readers wrote in with comments about
last week’s question about
Expected vs. Actual Wins
:

Regarding whether
Wes Ferrell‘s
Hall of Fame case is enhanced by his
offensive production, Kevin Morse writes: "He’s certainly more
deserving than his Vet Committee-elected brother Rick."

Brian Simpson asks: "What about
Orel Hershiser?
I seem to
remember him being a fairly good hitter before he got hurt." Indeed,
Hershiser was pretty good with the stick for a pitcher. His best season was
1993, when he posted a 784 OPS (.356/.373/.411), but that was his only
season with an OPS over 600 in 50 or more plate appearances.

Mike Ritzema writes: "I read your article and I was wondering where
Darren Dreifort
would place. I saw his two bombs against Chicago last
year and it gives me hope that he’ll hit for his money, too."
Dreifort’s two bombs helped him to just a 520 OPS last year
(.210/.246/.274), his best year to date.

David (no last name given) inquires: "Interesting article about
historical pitchers hitting performances. Can those numbers be converted to
some familiar sabermetric figures–runs above average, games won v. average,
etc. Basically, how does a good hitting pitcher affect a team’s ability to
win?"

Great question. The upper limit seems to be about 20 runs, for the very best
hitting pitching seasons, as shown in the following chart (PMLV is the
number of runs contributed on offense above what a league average pitcher
would have hit, adjusted for park and league):


YEAR


NAME


TEA


LG


PA


AVG


OBP


SLG


PMLV


1935


Wes Ferrell


BOS


A


171


.347


.427


.533


28.1


1955


Don Newcombe


BRO


N


124


.359


.395


.632


25.6


1965


Don Drysdale


LA


N


136


.300


.331


.508


25.6


1925


Walter Johnson


WAS


A


101


.433


.455


.577


24.1


1923


George Uhle


CLE


A


151


.361


.391


.472


22.4


1958


Warren Spahn


MIL


N


117


.333


.385


.463


22.1


1930


Red Lucas


CIN


N


130


.336


.423


.442


22.1


1931


Wes Ferrell


CLE


A


126


.319


.373


.621


22.0


1930


Red Ruffing


NY


A


106


.374


.415


.596


20.9


1923


Jack Bentley


NY


N


92


.427


.446


.573


20.4


1959


Don Newcombe


CIN


N


122


.305


.402


.410


20.2


1950


Bob Lemon


CLE


A


150


.272


.340


.485


20.0


1943


Schoolboy Rowe


PHI


N


136


.300


.382


.458


20.0

In today’s game, pitchers don’t throw as many innings or complete games, and
rarely would get a chance to bat often enough to clear 20 runs of value.
Hershiser’s 1993 was worth about 13.5 runs, and that’s about the top end
for the past couple of decades.

Keith Woolner is an author of Baseball Prospectus. Contact him by

clicking here
.

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