Calculate FIP and related metrics for any set of data

This function allows you to calculate FIP and related metrics for any given set of data, provided the right variables are in the data set. The function currently returns both FIP per inning pitched, wOBA against (based on batters faced), and wOBA against per instance of fair contact.

Usage

fip_plus(df)

Arguments

df

A data frame of statistics that includes, at a minimum, the following columns: IP (innings pitched), BF (batters faced), 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 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
GS	numeric	Games started
W	numeric	Wins
L	numeric	Losses
SV	numeric	Saves
IP	numeric	Innings pitched
H	numeric	Hits allowed
R	numeric	Runs allowed
ER	numeric	Earned runs allowed
uBB	numeric	Unintentional walks allowed
BB	numeric	Walks (bases on balls) allowed
SO	numeric	Strikeouts
HR	numeric	Home runs allowed
HBP	numeric	Hit batters
ERA	numeric	Earned run average
AB	numeric	At-bats against
X1B	numeric	Singles allowed
X2B	numeric	Doubles allowed
X3B	numeric	Triples allowed
IBB	numeric	Intentional walks allowed
GDP	numeric	Grounded into double plays induced
SF	numeric	Sacrifice flies allowed
SB	numeric	Stolen bases allowed
CS	numeric	Caught stealing
PO	numeric	Pickoffs
BF	numeric	Batters faced
Pit	numeric	Pitches thrown
Str	numeric	Strikes thrown
StL	numeric	Strikes looking (called)
StS	numeric	Strikes swinging (whiffs)
GB.FB	numeric	Ground ball to fly ball ratio
LD	numeric	Line drives allowed
PU	numeric	Pop ups (infield fly) induced
WHIP	numeric	Walks plus hits per inning pitched
BAbip	numeric	Batting average on balls in play allowed
SO9	numeric	Strikeouts per nine innings
SO.W	numeric	Strikeout-to-walk ratio
SO_perc	numeric	Strikeout percentage
uBB_perc	numeric	Unintentional walk percentage
SO_uBB	numeric	Strikeout percentage minus unintentional walk percentage
FIP	numeric	Fielding independent pitching
wOBA_against	numeric	Weighted on-base average against (based on batters faced)
wOBA_CON_against	numeric	Weighted on-base average against per instance of fair contact

Examples

# \donttest{
  try({
    df <- bref_daily_pitcher("2015-04-05", "2015-04-30")
    fip_plus(df)
  })
#> ── MLB Daily Pitcher data from baseball-reference.com ──────────────────
#> ℹ Data updated: 2026-06-24 02:05:32 UTC
#> # A tibble: 453 × 49
#>    bbref_id season Name    Age Level Team      G    GS     W     L    SV
#>    <chr>     <int> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 hembrhe…   2015 Heat…    26 Maj-… Bost…     1     0    NA    NA    NA
#>  2 hollade…   2015 Dere…    28 Maj-… Texas     1     1    NA     1    NA
#>  3 edwarjo…   2015 Jon …    27 Maj-… Texas     1     0    NA    NA    NA
#>  4 mazzoco…   2015 Cory…    25 Maj-… San …     2     0    NA    NA    NA
#>  5 gonzase…   2015 Seve…    22 Maj-… Phil…     1     1    NA     1    NA
#>  6 cornejo…   2015 John…    26 Maj-… Atla…     1     0    NA    NA    NA
#>  7 rearich…   2015 Chri…    27 Maj-… San …     5     0    NA    NA    NA
#>  8 vealdo01   2015 Donn…    30 Maj-… Atla…     1     0    NA    NA    NA
#>  9 rondojo…   2015 Jorg…    27 Maj-… Colo…     1     0    NA    NA    NA
#> 10 ranauan…   2015 Anth…    25 Maj-… Texas     1     1    NA     1    NA
#> # ℹ 443 more rows
#> # ℹ 38 more variables: IP <dbl>, H <dbl>, R <dbl>, ER <dbl>, uBB <dbl>,
#> #   BB <dbl>, SO <dbl>, HR <dbl>, HBP <dbl>, ERA <dbl>, AB <dbl>,
#> #   X1B <dbl>, X2B <dbl>, X3B <dbl>, IBB <dbl>, GDP <dbl>, SF <dbl>,
#> #   SB <dbl>, CS <dbl>, PO <dbl>, BF <dbl>, Pit <dbl>, Str <dbl>,
#> #   StL <dbl>, StS <dbl>, GB.FB <dbl>, LD <dbl>, PU <dbl>, WHIP <dbl>,
#> #   BAbip <dbl>, SO9 <dbl>, SO.W <dbl>, SO_perc <dbl>, …
# }