Load wehoop WNBA play-by-play — load_wnba

helper that loads multiple seasons from the data repo either into memory or writes it into a db using some forwarded arguments in the dots

Usage

load_wnba_pbp(
  seasons = most_recent_wnba_season(),
  ...,
  dbConnection = NULL,
  tablename = NULL
)

Arguments

seasons: A vector of 4-digit years associated with given WNBA seasons. (Min: 2002)
...: Additional arguments passed to an underlying function that writes the season data into a database (used by update_wnba_db()).
dbConnection: A DBIConnection object, as returned by DBI::dbConnect()
tablename: The name of the play by play data table within the database

Value

A dataframe with 42 columns

col_name	description
shooting_play	Logical value (TRUE/FALSE) indicating whether the play was a shooting play
sequence_number	Sequence number is supposed to represent a shot-possession, examine the last two numbers to see if there are multiple events that occur within the same shot-possession. A shot-possession is basically any sequence of plays until there is a shot, change in possession, and probably things like technical fouls and the like. So as soon as a shot goes up, a new sequence starts regardless, even if the shooting team retains possession via offensive or deadball rebound. The first portion of the number is usually time related (i.e. the numeric representation of when the sequence started, from a seconds remaining in the period perspective or so)
period_display_value	Long form of period (1st quarter, 2nd Quarter, OT, etc.)
period_number	The numeric period of play in the game
home_score	Home score at the time of the play
coordinate_x	The entire scale is a rectangle of size 25x47, intended as a half-court representation of the basketball court (i.e. on the side of the offense), with each coordinate unit representing a foot. It appears that the basket is roughly represented as the (25, 0) point. This is a nonsensical definition when considering that the basket overhangs the court, with the backboard aligned 48 inches from the baseline, then the center of the hoop being roughly 11 inches from there. This is an idiosyncracy of either sensor placement or software and data entry. Use your best judgement in making your charts, I think you will find that making some translations will be helpful.
coordinate_y
scoring_play	Logical value (TRUE/FALSE) indicating whether the play was a play on which the offense scored
clock_display_value	Time left within the period
team_id	Unique team identification number for the offensive team
type_id	Unique play type identifcation number
type_text	Play type text description
away_score	Away score at the time of the play
id	Unique play identifcation number
text	Text description of the play
score_value	The points value of the shot taken
participants_0_athlete_id	Unique player identification number
participants_1_athlete_id	Unique player identification number
participants_2_athlete_id	Unique player identification number
type_abbreviation	Play type abbreviation
season	Season of the game
season_type	Season type of the game, 1 is pre-season, 2 is regular season, 3 is post-season, 4 is off-season
away_team_id	Unique away team identification number
away_team_name	Away team name
away_team_mascot	Away team mascot
away_team_abbrev	Text abbreviation for the away team
away_team_name_alt	Alternate versions of the away team abbreviation
home_team_id	Unique home team identification number
home_team_name	home team name
home_team_mascot	home team mascot
home_team_abbrev	Text abbreviation for the home team
home_team_name_alt	Alternate versions of the home team abbreviation
home_team_spread	The game spread with respect to the home team
game_spread	Game spread in (-X Team) format. There are almost none, I would recommend not trusting any of these three columns
home_favorite	Logical (TRUE/FALSE) indicating whether the home team is favored
clock_minutes	Clock minutes split from seconds for developer convenience
clock_seconds	Clock seconds split from minutes for developer convenience
half	Half of the game
lag_half	A lag column on the half
lead_half	A lead column on the half
game_play_number	Game play number
game_id	Unique identifier for the game event

Examples

# \donttest{
  try(load_wnba_pbp())
#> ──────────────────────────────────────────────────────────────── wehoop 3.0.0 ──
#> # A tibble: 59,829 × 64
#>    game_play_number        id sequence_number type_id type_text text  away_score
#>               <int>     <dbl>           <int>   <int> <chr>     <chr>      <int>
#>  1                1   4.02e 9               4     615 Jumpball  Nata…          0
#>  2                2   4.02e 9               8     128 Driving … Oliv…          0
#>  3                3   4.02e 9               9     155 Defensiv… Jess…          0
#>  4                4   4.02e10              10     119 Driving … Awak…          0
#>  5                5   4.02e10              14     132 Step Bac… Nia …          3
#>  6                6   4.02e10              16      90 Out of B… Paig…          3
#>  7                7   4.02e10              17      92 Jump Shot Kayl…          6
#>  8                8   4.02e10              20      92 Jump Shot Awak…          6
#>  9                9   4.02e10              21     155 Defensiv… Oliv…          6
#> 10               10   4.02e10              22      44 Shooting… Paig…          6
#> # ℹ 59,819 more rows
#> # ℹ 57 more variables: home_score <int>, period_number <int>,
#> #   period_display_value <chr>, clock_display_value <chr>, scoring_play <lgl>,
#> #   score_value <int>, team_id <int>, athlete_id_1 <int>, athlete_id_2 <int>,
#> #   athlete_id_3 <int>, wallclock <chr>, shooting_play <lgl>,
#> #   coordinate_x_raw <dbl>, coordinate_y_raw <dbl>, points_attempted <int>,
#> #   short_description <chr>, game_id <int>, season <int>, season_type <int>, …
# }