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Towards the beginning
of this lecture,

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we stated that the
goal of a baseball team

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is to make the playoffs and
we built predictive models

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to achieve this goal.

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But why isn't the goal
of a baseball team

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to win the playoffs or
win the World Series?

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Billy Beane and Paul
Depodesta see their job

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as making sure the team
makes it to the playoffs,

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and after that,
all bets are off.

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The A's made it to the playoffs
four years in a row-- 2000,

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2001, 2002, and 2003-- but they
didn't win the World Series.

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Why not?

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In Moneyball, they say that
"over a long season luck

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evens out, and skill
shines through.

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But in a series of
three out of five,

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or even four out of seven,
anything can happen."

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In other words, the playoffs
suffer from the sample size

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problem.

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There are not enough games to
make any statistical claims.

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Let's see if we can verify
this using our data set.

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The number of teams
in the playoffs

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has changed over the years.

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So let's only use the
years with eight teams

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in the playoffs, which was the
number of teams in the playoffs

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in 2002, the year
Moneyball discusses.

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We can compute the correlation
between whether or not

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the team wins the World
Series-- a binary variable--

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and the number of
regular season wins,

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since we would expect
teams with more wins

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to be more likely to
win the World Series.

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This correlation is
0.03, which is very low.

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So it turns out that winning
regular season games gets you

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to the playoffs, but in
the playoffs, there too

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few games for luck to even out.

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Next week, we'll discuss
logistic regression,

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which we'll be able to use
to predict whether or not

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the team will win
the World Series.