wOBA

Weighted on-base average (wOBA) for hitters from the
 2022 Major League Baseball (MLB) season. Standard errors are
 calculated by modeling hitting outcomes as multinomially
 distributed and plugging in empirical proportions as the &#8220;true&#8221;
 outcome probabilities. To handle small sample sizes, standard
 errors are lower bounded by the errors that would be obtained using
 league-wide proportions rather than the plug-in estimates.

data

Provides simple, fast, and stable functions to fit the normal
means model using empirical Bayes. For available models and details, see
function ebnm(). A detailed introduction to the package is provided
by Willwerscheid and Stephens (2021) <arXiv:2110.00152>.

Peter Carbonetto

ebnm

Solve the Empirical Bayes Normal Means Problem

Jason Willwerscheid

Matthew Stephens

Andrew Goldstein

Yusha Liu

wOBA function

<code>wOBA</code> is a data frame with 688 rows and 6 columns:<dl> <dt>FanGraphsID</dt>
<dd>The hitter's FanGraphs identifier.</dd>
 <dt>Name</dt>
<dd>The hitter's name.</dd> <dt>Team</dt>
<dd>The hitter's MLB team (given as a three-letter code) or
 <code>NA</code> if the hitter played for multiple teams.</dd> <dt>PA</dt>
<dd>The hitter's number of plate appearances over the 2022 season.</dd> <dt>x</dt>
<dd>The hitter's wOBA over the 2022 season.</dd>
 <dt>s</dt>
<dd>The standard error for the hitter's wOBA.</dd>
</dl>

Format

2022 MLB wOBA Data — wOBA

<code>wOBA</code> is a data frame with 688 rows and 6 columns:<dl>

 <dt>FanGraphsID</dt>
<dd>The hitter's FanGraphs identifier.</dd>


 <dt>Name</dt>
<dd>The hitter's name.</dd>

 <dt>Team</dt>
<dd>The hitter's MLB team (given as a three-letter code) or
 <code>NA</code> if the hitter played for multiple teams.</dd>

 <dt>PA</dt>
<dd>The hitter's number of plate appearances over the 2022 season.</dd>

 <dt>x</dt>
<dd>The hitter's wOBA over the 2022 season.</dd>


 <dt>s</dt>
<dd>The standard error for the hitter's wOBA.</dd>


</dl>

wOBA: 2022 MLB wOBA Data

Description

Arguments

Format

Examples