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
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
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
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
load_wnba_rosters_manifest() returns the per-season manifest
CSV (season, row_count, generated_at_utc, source_endpoint) for
the rosters release tag without downloading any season's full data.
load_wnba_player_stats_manifest() returns the per-season
manifest CSV (season, row_count, generated_at_utc,
source_endpoint) for the player season stats release tag without
downloading any season's full data.
load_wnba_team_stats_manifest() returns the per-season
manifest CSV (season, row_count, generated_at_utc,
source_endpoint) for the team season stats release tag without
downloading any season's full data.
load_wnba_standings_manifest() returns the per-season
manifest CSV (season, row_count, generated_at_utc,
source_endpoint) for the standings release tag without downloading
any season's full data.
load_wnba_draft_manifest() returns the per-season manifest
CSV (season, row_count, generated_at_utc, source_endpoint) for
the draft release tag without downloading any season's full data.
load_wnba_shots_manifest() returns the per-season manifest
CSV (season, row_count, generated_at_utc, source_endpoint) for
the shots release tag without downloading any season's full data.
load_wnba_game_rosters_manifest() returns the per-season
manifest CSV (season, row_count, generated_at_utc,
source_endpoint) for the game rosters release tag without downloading
any season's full data.
load_wnba_officials_manifest() returns the per-season
manifest CSV (season, row_count, generated_at_utc,
source_endpoint) for the officials release tag without downloading
any season's full data.
Loads season-level WNBA team rosters scraped from ESPN. One row
per athlete-team-season triple. Backed by the wehoop-wnba-data pipeline
that reads raw JSONs from wehoop-wnba-raw and publishes parquet/rds
artifacts to the espn_wnba_rosters release tag.
Loads season-level WNBA player statistics scraped from ESPN.
One row per athlete-team-season-statistic-grouping. Backed by the
wehoop-wnba-data pipeline that reads raw JSONs from wehoop-wnba-raw
and publishes parquet/rds artifacts to the
espn_wnba_player_season_stats release tag.
Loads season-level WNBA team statistics scraped from ESPN.
One row per team-season-statistic-grouping. Backed by the
wehoop-wnba-data pipeline that reads raw JSONs from wehoop-wnba-raw
and publishes parquet/rds artifacts to the
espn_wnba_team_season_stats release tag.
Loads season-level WNBA standings scraped from ESPN. One row
per team-season. Backed by the wehoop-wnba-data pipeline that reads
raw JSONs from wehoop-wnba-raw and publishes parquet/rds artifacts to
the espn_wnba_standings release tag.
Loads season-level WNBA draft picks scraped from ESPN. One
row per pick. Backed by the wehoop-wnba-data pipeline that reads raw
JSONs from wehoop-wnba-raw and publishes parquet/rds artifacts to the
espn_wnba_draft release tag.
Loads shot events parsed from ESPN WNBA play-by-play feeds.
One row per shot attempt (made or missed), with court coordinates and
shot metadata. Backed by the wehoop-wnba-data pipeline that reads raw
JSONs from wehoop-wnba-raw and publishes parquet/rds artifacts to the
espn_wnba_shots release tag.
Loads per-game rosters scraped from ESPN WNBA box scores. One
row per athlete-team-game triple, with athlete identifiers, jersey,
position, starter flag, and DNP status. Backed by the wehoop-wnba-data
pipeline that reads raw JSONs from wehoop-wnba-raw and publishes
parquet/rds artifacts to the espn_wnba_game_rosters release tag.
Loads game-level officials data scraped from ESPN WNBA summary
feeds. One row per official-game pair. Backed by the wehoop-wnba-data
pipeline that reads raw JSONs from wehoop-wnba-raw and publishes
parquet/rds artifacts to the espn_wnba_officials release tag.
Loads ESPN WNBA athlete core records – identity and
biographical fields, one row per athlete who appeared in the season.
Backed by the wehoop-wnba-data pipeline that reads raw JSONs from
wehoop-wnba-raw and publishes parquet/rds artifacts to the
espn_wnba_player_core release tag.
This is the only source of athlete bio in the pipeline: the player season stats payload carries no identity at all – not even the athlete id.
Two properties of the source are worth knowing before joining:
current_team_idis the athlete's CURRENT team, not their team in the requested season. Season team lives inload_wnba_player_box()/load_wnba_player_stats().Bio (height / weight / jersey) is a current snapshot that ESPN overwrites in place; it is not era-correct for a historical season. The season dimension here is participation, not the bio's vintage.
Field coverage is era-dependent by nature – headshots exist only for modern players, while college and date of birth thin out the other way.
Usage
load_wnba_pbp(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_team_box(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_player_box(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_schedule(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_rosters_manifest()
load_wnba_player_stats_manifest()
load_wnba_team_stats_manifest()
load_wnba_standings_manifest()
load_wnba_draft_manifest()
load_wnba_shots_manifest()
load_wnba_game_rosters_manifest()
load_wnba_officials_manifest()
load_wnba_rosters(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_player_stats(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_team_stats(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_standings(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_draft(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_shots(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_game_rosters(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_officials(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)
load_wnba_player_core(
seasons = most_recent_wnba_season(),
...,
dbConnection = NULL,
tablename = NULL
)Arguments
- seasons
A vector of 4-digit years associated with given WNBA seasons. (Min: 2003)
- ...
Additional arguments passed to an underlying function that writes the season data into a database.
- dbConnection
A
DBIConnectionobject, as returned byDBI::dbConnect()- tablename
The name of the player core 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, passed through verbatim from ESPN. Note: ESPN labels the free-throw play TYPE "MadeFreeThrow" for made AND missed free throws; filter makes vs. misses with scoring_play (TRUE = made), not type_text |
| 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 (1 / 2 / 3). Set to the attempt's value even on misses (a missed free throw still carries 1); use scoring_play to identify points actually scored |
| 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 |
Returns a tibble
Returns a tibble
Returns a tibble
Returns a wehoop_data tibble with one row per athlete-team-season.
Returns a wehoop_data tibble of player season stats.
Returns a wehoop_data tibble of team season stats.
Columns as documented in the shared basketball_load_wbb_team_stats_schema table.
Returns a wehoop_data tibble of team standings.
Columns as documented in the shared basketball_load_wbb_standings_schema table.
Returns a wehoop_data tibble of WNBA draft picks.
| col_name | types | description |
| season | integer | Season identifier (4-digit year or 'YYYY-YY' string). |
| round | integer | Tournament / playoff round. |
| pick | integer | Pick. |
| overall | integer | Overall. |
| team_id | character | Unique team identifier. |
| team_display_name | character | Full team display name. |
| athlete_id | character | Unique athlete identifier (ESPN). |
| athlete_display_name | character | Athlete display name (full). |
| athlete_position | character | Athlete position. |
| college_id | character | Unique identifier for college. |
| college_name | character | College name. |
Returns a wehoop_data tibble with one row per shot attempt.
Columns as documented in the shared basketball_load_wbb_shots_schema table.
Returns a wehoop_data tibble with one row per athlete-team-game.
Columns as documented in the shared basketball_load_wbb_game_rosters_schema table.
Returns a wehoop_data tibble with one row per official-game pair.
Columns as documented in the shared basketball_load_wbb_officials_schema table.
Returns a wehoop_data tibble of athlete core records.
Examples
# \donttest{
try(load_wnba_pbp())
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 135,650 × 67
#> 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 6 615 Jumpball Isab… 0
#> 2 2 4.02e 9 3 92 Jump Shot Diam… 0
#> 3 3 4.02e 9 5 155 Defensiv… Juli… 0
#> 4 4 4.02e 9 9 92 Jump Shot Isab… 0
#> 5 5 4.02e10 10 155 Defensiv… Sun … 0
#> 6 6 4.02e10 12 63 Lost Bal… Aali… 0
#> 7 7 4.02e10 14 110 Driving … Kiki… 2
#> 8 8 4.02e10 15 131 Pullup J… Char… 2
#> 9 9 4.02e10 16 92 Jump Shot Kia … 2
#> 10 10 4.02e10 17 155 Defensiv… Leil… 2
#> # ℹ 135,640 more rows
#> # ℹ 60 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>, …
# }
# \donttest{
try(load_wnba_team_box())
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 664 × 59
#> game_id season season_type game_date game_date_time team_id team_uid
#> <int> <int> <int> <date> <dttm> <int> <chr>
#> 1 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 131935 s:40~l:5…
#> 2 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 18 s:40~l:5…
#> 3 401857216 2026 2 2026-09-24 2026-09-24 19:30:00 19 s:40~l:5…
#> 4 401857216 2026 2 2026-09-24 2026-09-24 19:30:00 16 s:40~l:5…
#> 5 401857217 2026 2 2026-09-24 2026-09-24 20:00:00 5 s:40~l:5…
#> 6 401857217 2026 2 2026-09-24 2026-09-24 20:00:00 8 s:40~l:5…
#> 7 401857218 2026 2 2026-09-24 2026-09-24 22:00:00 129689 s:40~l:5…
#> 8 401857218 2026 2 2026-09-24 2026-09-24 22:00:00 6 s:40~l:5…
#> 9 401857219 2026 2 2026-09-24 2026-09-24 22:00:00 17 s:40~l:5…
#> 10 401857219 2026 2 2026-09-24 2026-09-24 22:00:00 11 s:40~l:5…
#> # ℹ 654 more rows
#> # ℹ 52 more variables: team_slug <chr>, team_location <chr>, team_name <chr>,
#> # team_abbreviation <chr>, team_display_name <chr>,
#> # team_short_display_name <chr>, team_color <chr>,
#> # team_alternate_color <chr>, team_logo <chr>, team_home_away <chr>,
#> # team_score <int>, team_winner <lgl>, assists <int>, blocks <int>,
#> # defensive_rebounds <int>, fast_break_points <chr>, field_goal_pct <dbl>, …
# }
# \donttest{
try(load_wnba_player_box())
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 8,051 × 57
#> game_id season season_type game_date game_date_time athlete_id
#> <int> <int> <int> <date> <dttm> <int>
#> 1 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 2566453
#> 2 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 5345444
#> 3 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 3142327
#> 4 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 4001679
#> 5 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 4565505
#> 6 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 4434020
#> 7 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 4398766
#> 8 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 5364343
#> 9 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 3910470
#> 10 401857215 2026 2 2026-09-24 2026-09-24 19:00:00 4398768
#> # ℹ 8,041 more rows
#> # ℹ 51 more variables: athlete_display_name <chr>, team_id <int>,
#> # team_name <chr>, team_location <chr>, team_short_display_name <chr>,
#> # minutes <dbl>, field_goals_made <int>, field_goals_attempted <int>,
#> # three_point_field_goals_made <int>,
#> # three_point_field_goals_attempted <int>, free_throws_made <int>,
#> # free_throws_attempted <int>, offensive_rebounds <int>, …
# }
# \donttest{
try(load_wnba_schedule())
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 362 × 77
#> id uid date attendance time_valid neutral_site conference_competition
#> <int> <chr> <chr> <dbl> <lgl> <lgl> <lgl>
#> 1 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 2 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 3 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 4 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 5 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 6 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 7 4.02e8 s:40… 2026… 0 TRUE FALSE FALSE
#> 8 4.02e8 s:40… 2026… 0 FALSE FALSE FALSE
#> 9 4.02e8 s:40… 2026… 0 FALSE FALSE FALSE
#> 10 4.02e8 s:40… 2026… 0 FALSE FALSE FALSE
#> # ℹ 352 more rows
#> # ℹ 70 more variables: play_by_play_available <lgl>, recent <lgl>,
#> # start_date <chr>, broadcast <chr>, highlights <chr>, notes_type <chr>,
#> # notes_headline <chr>, broadcast_market <chr>, broadcast_name <chr>,
#> # type_id <int>, type_abbreviation <chr>, venue_id <int>,
#> # venue_full_name <chr>, venue_address_city <chr>, venue_address_state <chr>,
#> # venue_indoor <lgl>, status_clock <dbl>, status_display_clock <chr>, …
# }
# \donttest{
try(load_wnba_rosters(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 221 × 36
#> season team_id team_slug team_abbreviation team_display_name
#> <int> <int> <chr> <chr> <chr>
#> 1 2026 11 NA PHX Phoenix Mercury
#> 2 2026 11 NA PHX Phoenix Mercury
#> 3 2026 11 NA PHX Phoenix Mercury
#> 4 2026 11 NA PHX Phoenix Mercury
#> 5 2026 11 NA PHX Phoenix Mercury
#> 6 2026 11 NA PHX Phoenix Mercury
#> 7 2026 11 NA PHX Phoenix Mercury
#> 8 2026 11 NA PHX Phoenix Mercury
#> 9 2026 11 NA PHX Phoenix Mercury
#> 10 2026 11 NA PHX Phoenix Mercury
#> # ℹ 211 more rows
#> # ℹ 31 more variables: team_short_display_name <chr>, team_color <chr>,
#> # team_alternate_color <chr>, team_logo <chr>, athlete_id <chr>, uid <chr>,
#> # guid <chr>, full_name <chr>, display_name <chr>, short_name <chr>,
#> # first_name <chr>, last_name <chr>, jersey <chr>,
#> # position_abbreviation <chr>, position_name <chr>, position_id <chr>,
#> # height <chr>, weight <chr>, age <chr>, date_of_birth <chr>, …
# }
# \donttest{
try(load_wnba_player_stats(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 10,396 × 16
#> season athlete_id athlete_display_name athlete_first_name athlete_last_name
#> <int> <int> <chr> <chr> <chr>
#> 1 2026 1054 Tiffany Hayes Tiffany Hayes
#> 2 2026 1054 Tiffany Hayes Tiffany Hayes
#> 3 2026 1054 Tiffany Hayes Tiffany Hayes
#> 4 2026 1054 Tiffany Hayes Tiffany Hayes
#> 5 2026 1054 Tiffany Hayes Tiffany Hayes
#> 6 2026 1054 Tiffany Hayes Tiffany Hayes
#> 7 2026 1054 Tiffany Hayes Tiffany Hayes
#> 8 2026 1054 Tiffany Hayes Tiffany Hayes
#> 9 2026 1054 Tiffany Hayes Tiffany Hayes
#> 10 2026 1054 Tiffany Hayes Tiffany Hayes
#> # ℹ 10,386 more rows
#> # ℹ 11 more variables: athlete_position_abbreviation <chr>,
#> # athlete_jersey <chr>, team_id <int>, team_display_name <chr>,
#> # category <chr>, stat_label <chr>, stat_name <chr>, stat_display_name <chr>,
#> # stat_description <chr>, display_value <chr>, value <dbl>
# }
# \donttest{
try(load_wnba_team_stats(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 675 × 16
#> season team_id team_slug team_abbreviation team_display_name
#> <int> <int> <chr> <chr> <chr>
#> 1 2026 11 NA PHX Phoenix Mercury
#> 2 2026 11 NA PHX Phoenix Mercury
#> 3 2026 11 NA PHX Phoenix Mercury
#> 4 2026 11 NA PHX Phoenix Mercury
#> 5 2026 11 NA PHX Phoenix Mercury
#> 6 2026 11 NA PHX Phoenix Mercury
#> 7 2026 11 NA PHX Phoenix Mercury
#> 8 2026 11 NA PHX Phoenix Mercury
#> 9 2026 11 NA PHX Phoenix Mercury
#> 10 2026 11 NA PHX Phoenix Mercury
#> # ℹ 665 more rows
#> # ℹ 11 more variables: team_short_display_name <chr>, team_color <chr>,
#> # team_alternate_color <chr>, team_logo <chr>, category <chr>,
#> # stat_label <chr>, stat_name <chr>, stat_display_name <chr>,
#> # stat_description <chr>, display_value <chr>, value <dbl>
# }
# \donttest{
try(load_wnba_standings(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 345 × 24
#> season group_id group_name group_abbreviation group_short_name team_id
#> <int> <chr> <chr> <chr> <chr> <int>
#> 1 2026 1 Eastern Conferen… E NA 20
#> 2 2026 1 Eastern Conferen… E NA 20
#> 3 2026 1 Eastern Conferen… E NA 20
#> 4 2026 1 Eastern Conferen… E NA 20
#> 5 2026 1 Eastern Conferen… E NA 20
#> 6 2026 1 Eastern Conferen… E NA 20
#> 7 2026 1 Eastern Conferen… E NA 20
#> 8 2026 1 Eastern Conferen… E NA 20
#> 9 2026 1 Eastern Conferen… E NA 20
#> 10 2026 1 Eastern Conferen… E NA 20
#> # ℹ 335 more rows
#> # ℹ 18 more variables: team_uid <chr>, team_slug <chr>, team_location <chr>,
#> # team_name <chr>, team_abbreviation <chr>, team_display_name <chr>,
#> # team_short_display_name <chr>, team_color <chr>,
#> # team_alternate_color <chr>, team_logo <chr>, stat_name <chr>,
#> # stat_display_name <chr>, stat_short_display_name <chr>,
#> # stat_description <chr>, stat_abbreviation <chr>, stat_type <chr>, …
# }
# \donttest{
try(load_wnba_draft(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 45 × 35
#> season round round_display_name pick overall_pick pick_traded pick_notes
#> <int> <int> <chr> <int> <int> <chr> <chr>
#> 1 2026 1 NA 1 1 FALSE NA
#> 2 2026 1 NA 2 2 TRUE NA
#> 3 2026 1 NA 3 3 TRUE NA
#> 4 2026 1 NA 4 4 FALSE NA
#> 5 2026 1 NA 5 5 TRUE NA
#> 6 2026 1 NA 6 6 FALSE NA
#> 7 2026 1 NA 7 7 FALSE NA
#> 8 2026 1 NA 8 8 TRUE NA
#> 9 2026 1 NA 9 9 TRUE NA
#> 10 2026 1 NA 10 10 FALSE NA
#> # ℹ 35 more rows
#> # ℹ 28 more variables: athlete_id <int>, athlete_uid <chr>, athlete_guid <chr>,
#> # athlete_first_name <chr>, athlete_last_name <chr>, athlete_full_name <chr>,
#> # athlete_display_name <chr>, athlete_short_name <chr>, athlete_height <chr>,
#> # athlete_weight <chr>, athlete_position_abbreviation <chr>,
#> # athlete_position_name <chr>, athlete_headshot_href <chr>, college_id <int>,
#> # college_name <chr>, college_short_name <chr>, college_abbreviation <chr>, …
# }
# \donttest{
try(load_wnba_shots(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 59,413 × 20
#> game_id season period_number clock_display_value team_id athlete_id_1
#> <int> <int> <int> <chr> <int> <int>
#> 1 401857215 2026 1 9:47 18 4433635
#> 2 401857215 2026 1 9:26 131935 2566453
#> 3 401857215 2026 1 8:46 131935 4565505
#> 4 401857215 2026 1 8:32 18 4703609
#> 5 401857215 2026 1 8:20 131935 3142327
#> 6 401857215 2026 1 8:07 18 5105732
#> 7 401857215 2026 1 7:50 131935 2566453
#> 8 401857215 2026 1 7:31 131935 5345444
#> 9 401857215 2026 1 7:20 131935 4565505
#> 10 401857215 2026 1 7:19 131935 4565505
#> # ℹ 59,403 more rows
#> # ℹ 14 more variables: athlete_id_2 <int>, type_id <int>, type_text <chr>,
#> # scoring_play <lgl>, score_value <int>, coordinate_x <dbl>,
#> # coordinate_y <dbl>, coordinate_x_raw <dbl>, coordinate_y_raw <dbl>,
#> # athlete_name_1 <chr>, athlete_name_2 <chr>, team_name <chr>,
#> # team_mascot <chr>, team_abbrev <chr>
# }
# \donttest{
try(load_wnba_game_rosters(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 8,051 × 22
#> season game_id team_id team_slug team_abbreviation team_display_name
#> <int> <chr> <int> <chr> <chr> <chr>
#> 1 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 2 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 3 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 4 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 5 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 6 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 7 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 8 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 9 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> 10 2026 401856890 18 connecticut-sun CON Connecticut Sun
#> # ℹ 8,041 more rows
#> # ℹ 16 more variables: home_away <chr>, athlete_id <int>, athlete_uid <chr>,
#> # athlete_guid <chr>, athlete_display_name <chr>, athlete_short_name <chr>,
#> # athlete_first_name <chr>, athlete_last_name <chr>, athlete_jersey <chr>,
#> # athlete_position <chr>, athlete_headshot <chr>, starter <lgl>,
#> # did_not_play <lgl>, active <lgl>, ejected <lgl>, reason <chr>
# }
# \donttest{
try(load_wnba_officials(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 997 × 11
#> season game_id official_id official_uid official_full_name
#> <int> <chr> <int> <chr> <chr>
#> 1 2026 401856890 52042 NA Roy Gulbeyan
#> 2 2026 401856890 3951614 NA Ryan Sassano
#> 3 2026 401856890 4236122 NA Tyler Mirkovich
#> 4 2026 401856891 52044 NA Fatou Cissoko-Stephens
#> 5 2026 401856891 52049 NA Charles Watson
#> 6 2026 401856891 4356548 NA Clare Simmons
#> 7 2026 401856892 1211 NA Angelica Suffren
#> 8 2026 401856892 5113092 NA Sarah Williams
#> 9 2026 401856892 5184398 NA Josh Reed
#> 10 2026 401856893 1183 NA Tim Greene
#> # ℹ 987 more rows
#> # ℹ 6 more variables: official_display_name <chr>, official_first_name <chr>,
#> # official_last_name <chr>, official_order <int>, position_name <chr>,
#> # position_display_name <chr>
# }
# \donttest{
try(load_wnba_player_core(seasons = most_recent_wnba_season()))
#> ─────────────────────────────────────────────────────────── wehoop 3.0.0.9000 ──
#> # A tibble: 244 × 36
#> season athlete_id guid uid slug type first_name last_name full_name
#> <int> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2026 869 74bfe609-… s:40… dewa… bask… DeWanna Bonner DeWanna …
#> 2 2026 887 c74956ad-… s:40… sami… bask… Sami Whitcomb Sami Whi…
#> 3 2026 924 09609790-… s:40… alys… bask… Alysha Clark Alysha C…
#> 4 2026 981 1d736065-… s:40… cour… bask… Courtney Vandersl… Courtney…
#> 5 2026 1054 026e19c6-… s:40… tiff… bask… Tiffany Hayes Tiffany …
#> 6 2026 1068 759b52cb-… s:40… nnek… bask… Nneka Ogwumike Nneka Og…
#> 7 2026 1107 5530f9d2-… s:40… shey… bask… Shey Peddy Shey Ped…
#> 8 2026 2284331 3f0f0fd1-… s:40… emma… bask… Emma Cannon Emma Can…
#> 9 2026 2327695 cea6f839-… s:40… rebe… bask… Rebekah Gardner Rebekah …
#> 10 2026 2490553 40e7dc87-… s:40… brit… bask… Brittney Griner Brittney…
#> # ℹ 234 more rows
#> # ℹ 27 more variables: display_name <chr>, short_name <chr>, height <dbl>,
#> # display_height <chr>, weight <dbl>, display_weight <chr>, age <int>,
#> # date_of_birth <chr>, birth_city <chr>, birth_state <chr>,
#> # birth_country <chr>, jersey <chr>, position_id <int>, position_name <chr>,
#> # position_abbreviation <chr>, position_display_name <chr>, college_id <int>,
#> # current_team_id <int>, headshot_href <chr>, experience_years <int>, …
# }