Calculate wOBA and related metrics for any set of data

This function allows you to calculate wOBA for any given set of data, provided the right variables are in the data set. The function currently returns both wOBA per plate appearance on wOBA per instance of fair contact.

Usage

woba_plus(df)

Arguments

df

A data frame of statistics that includes, at a minimum, the following columns: uBB (unintentional walks), HBP (Hit By Pitch), X1B (singles), X2B (doubles), X3B (triples), HR (home runs), AB (at-bats), SH (sacrifice hits), SO (strike outs), and season.

Value

Returns a tibble with the wOBA factors calculated and the following columns:

col_name	types	description
bbref_id	character	Baseball-Reference player id
season	integer	Season (4-digit year)
Name	character	Player name
Age	numeric	Player age
Level	character	Level of play (e.g. MLB or minor-league level)
Team	character	Team name
G	numeric	Games played
PA	numeric	Plate appearances
AB	numeric	At-bats
R	numeric	Runs scored
H	numeric	Hits
X1B	numeric	Singles
X2B	numeric	Doubles
X3B	numeric	Triples
HR	numeric	Home runs
RBI	numeric	Runs batted in
BB	numeric	Walks (bases on balls)
IBB	numeric	Intentional walks
uBB	numeric	Unintentional walks (BB minus IBB)
SO	numeric	Strikeouts
HBP	numeric	Hit by pitch
SH	numeric	Sacrifice hits (bunts)
SF	numeric	Sacrifice flies
GDP	numeric	Grounded into double plays
SB	numeric	Stolen bases
CS	numeric	Caught stealing
BA	numeric	Batting average
OBP	numeric	On-base percentage
SLG	numeric	Slugging percentage
OPS	numeric	On-base plus slugging
wOBA	numeric	Weighted on-base average (per plate appearance)
wOBA_CON	numeric	Weighted on-base average per instance of fair contact

Examples

# \donttest{
 try({
   df <- bref_daily_batter("2015-08-01", "2015-10-03") 
   woba_plus(df)
 })
#> ── MLB Daily Batter data from baseball-reference.com ───────────────────
#> ℹ Data updated: 2026-06-12 14:10:08 UTC
#> # A tibble: 764 × 32
#>    bbref_id season Name    Age Level Team      G    PA    AB     R     H
#>    <chr>     <int> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 pindebr…   2015 Bran…    26 Maj-… New …     1     1     1     0     1
#>  2 severpe…   2015 Pedr…    21 Maj-… Wash…     1     1     1     1     1
#>  3 bandyje…   2015 Jett…    25 Maj-… Los …     2     2     2     1     1
#>  4 norrida…   2015 Dani…    22 Maj-… Detr…     1     3     2     1     1
#>  5 hesslke…   2015 Keit…    26 Maj-… Ariz…     1     1     1     0     1
#>  6 noelri02   2015 Rico…    26 Maj-… New …    13     1     1     5     1
#>  7 torreca…   2015 Carl…    32 Maj-… New …     1     1     1     1     1
#>  8 garcija…   2015 Jaso…    22 Maj-… Balt…     1     1     0     0     0
#>  9 gallayo…   2015 Yova…    29 Maj-… Texas     1     2     2     0     1
#> 10 panikjo…   2015 Joe …    24 Maj-… San …     4    14    12     5     5
#> # ℹ 754 more rows
#> # ℹ 21 more variables: X1B <dbl>, X2B <dbl>, X3B <dbl>, HR <dbl>,
#> #   RBI <dbl>, BB <dbl>, IBB <dbl>, uBB <dbl>, SO <dbl>, HBP <dbl>,
#> #   SH <dbl>, SF <dbl>, GDP <dbl>, SB <dbl>, CS <dbl>, BA <dbl>,
#> #   OBP <dbl>, SLG <dbl>, OPS <dbl>, wOBA <dbl>, wOBA_CON <dbl>
# }