Scrape Pitcher Performance Data Over a Custom Time Frame

This function allows you to scrape basic pitcher statistics over a custom time frame. Data is sourced from Baseball-Reference.com.

Usage

bref_daily_pitcher(t1, t2)

Arguments

t1: First date data should be scraped from. Should take the form "YEAR-MONTH-DAY"
t2: Last date data should be scraped from. Should take the form "YEAR-MONTH-DAY"

Value

Returns a tibble of pitcher performance with the following columns:

col_name	types
bbref_id	character
season	integer
Name	character
Age	numeric
Level	character
Team	character
G	numeric
GS	numeric
W	numeric
L	numeric
SV	numeric
IP	numeric
H	numeric
R	numeric
ER	numeric
uBB	numeric
BB	numeric
SO	numeric
HR	numeric
HBP	numeric
ERA	numeric
AB	numeric
X1B	numeric
X2B	numeric
X3B	numeric
IBB	numeric
GDP	numeric
SF	numeric
SB	numeric
CS	numeric
PO	numeric
BF	numeric
Pit	numeric
Str	numeric
StL	numeric
StS	numeric
GB.FB	numeric
LD	numeric
PU	numeric
WHIP	numeric
BAbip	numeric
SO9	numeric
SO.W	numeric
SO_perc	numeric
uBB_perc	numeric
SO_uBB	numeric

Examples

# \donttest{
  try(bref_daily_pitcher("2015-05-10", "2015-06-20"))
#> ── MLB Daily Pitcher data from baseball-reference.com ──────────────────
#> ℹ Data updated: 2022-04-30 07:14:49 UTC
#> # A tibble: 511 × 46
#>    bbref_id season Name    Age Level Team      G    GS     W     L    SV
#>    <chr>     <int> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 430911     2015 Chri…    26 Maj-… Chic…     8     8     4     2    NA
#>  2 472551     2015 Max …    30 Maj-… Wash…     8     8     6     2    NA
#>  3 542866     2015 Mark…    36 Maj-… Toro…     8     8     3     2    NA
#>  4 502264     2015 Core…    29 Maj-… Clev…     8     8     3     4    NA
#>  5 346793     2015 Dall…    27 Maj-… Hous…     8     8     4     3    NA
#>  6 456379     2015 Jaco…    27 Maj-… New …     8     8     4     2    NA
#>  7 592102     2015 Jeff…    30 Maj-… Chic…     8     8     2     2    NA
#>  8 506693     2015 Gerr…    24 Maj-… Pitt…     8     8     7     1    NA
#>  9 501625     2015 Clay…    30 Maj-… Bost…     8     8     3     2    NA
#> 10 506560     2015 A.J.…    38 Maj-… Pitt…     8     8     5     2    NA
#> # … with 501 more rows, and 35 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>, uBB_perc <dbl>, SO_uBB <dbl>
# }