ESPN basketball endpoints -- WBB & WNBA
Saiem Gilani
Source: vignettes/espn-endpoints.Rmd
espn-endpoints.RmdWhat this vignette covers
If you’ve used wehoop before, you’ve probably reached
for espn_wbb_pbp(), espn_wnba_pbp(), and the
box score wrappers. Those get you the bulk of any analysis built around
individual games. The package now also wraps a much wider slice of
ESPN’s basketball API – team rosters, schedules, league news, athlete
biographies and gamelogs, in-game win probabilities, officials,
broadcast info, the WNBA draft, free agency, transactions, and
league-wide catalogs of venues, coaches, and statistical leaders. Around
180 ESPN endpoint wrappers in total, split between women’s college
basketball (espn_wbb_*) and the WNBA
(espn_wnba_*).
This vignette is a tour of what’s available and how to compose the pieces. Most of the chunks run live when the package website is built, so the tables below are real ESPN responses – and every one of them works the same way when you copy it into an interactive session.
A note on the API surface
ESPN exposes basketball data through three public, unauthenticated
API hosts, and wehoop reaches into each:
-
site.api.espn.com/apis/site/v2/sports/basketball/{league}is the most stable. It serves scoreboards, teams, rosters, schedules, news, injuries, standings, and player and team season stats. -
sports.core.api.espn.com/v2/sports/basketball/{league}carries the deeper resources: athlete indexes, per-event detail (odds, win probabilities, officials, broadcasts), seasons, venues, coaches, the WNBA draft, and transactions. Big collections paginate via$reflinks. -
site.web.api.espn.com/apis/common/v3/sports/basketball/{league}carries per-athlete deep detail – season overview, stats by category, game-by-game logs, situational splits. It’s the least stable of the three; older seasons sometimes return 404, and not every athlete is represented.
There’s a fourth host (cdn.espn.com/core) that surfaces
the same information as the site-v2 /summary endpoint we
already parse, so we don’t wrap it.
The league slugs in URL paths are
womens-college-basketball and wnba. Those only
matter if you’re building requests by hand.
Rate limits. ESPN doesn’t publish them. In practice,
requests arriving faster than about one per second occasionally come
back as HTTP 429 or as silently empty payloads. If you’re looping over
many games or athletes, drop a Sys.sleep(1) between
calls.
Proxies. ESPN wrappers don’t accept a per-call
proxy = argument; they call into the package’s HTTP layer
directly. Set the proxy once at the top of your session with
options(wehoop.proxy = "http://host:port") (or a list, for
authenticated proxies) and every ESPN call will pick it up
automatically.
What’s available, by use case
The tables below are grouped by what you’re likely trying to do. Function names are clickable on the pkgdown reference.
Game data
These all key off game_id (also called
event_id in some endpoints – they’re the same thing).
| Function | Returns |
|---|---|
espn_wbb_game_all() /
espn_wnba_game_all()
|
Full game summary as a named list |
espn_wbb_pbp() / espn_wnba_pbp()
|
Play-by-play |
espn_wbb_team_box() /
espn_wnba_team_box()
|
Team box score |
espn_wbb_player_box() /
espn_wnba_player_box()
|
Player box score |
espn_wbb_game_rosters() /
espn_wnba_game_rosters()
|
Game-day rosters |
Scoreboard, conferences, and league reference
| Function | Returns |
|---|---|
espn_wbb_scoreboard() /
espn_wnba_scoreboard()
|
Daily scoreboard |
espn_wbb_teams() / espn_wnba_teams()
|
All teams |
espn_wbb_conferences() /
espn_wnba_conferences()
|
Conferences |
espn_wbb_rankings() |
AP / coaches poll (WBB only – WNBA has no poll) |
espn_wbb_standings() /
espn_wnba_standings()
|
Conference / league standings |
espn_wbb_news() / espn_wnba_news()
|
League-wide news feed |
espn_wbb_calendar() /
espn_wnba_calendar()
|
Season calendar weeks |
Team detail
| Function | Returns |
|---|---|
espn_wbb_team() / espn_wnba_team()
|
Single-team info, record, coaches |
espn_wbb_team_roster() /
espn_wnba_team_roster()
|
Roster |
espn_wbb_team_schedule() /
espn_wnba_team_schedule()
|
Schedule |
espn_wbb_team_leaders() /
espn_wnba_team_leaders()
|
Statistical leaders |
espn_wbb_team_news() /
espn_wnba_team_news()
|
Team news feed |
espn_wbb_team_stats() /
espn_wnba_team_stats()
|
Team-level season stats |
espn_wbb_team_injuries() /
espn_wnba_team_injuries()
|
Team injury report |
espn_wbb_injuries() /
espn_wnba_injuries()
|
League-wide injury report |
Athlete detail
| Function | Returns |
|---|---|
espn_wbb_player_info() /
espn_wnba_player_info()
|
Bio and profile |
espn_wbb_player_overview() /
espn_wnba_player_overview()
|
Season overview (web-common-v3) |
espn_wbb_player_stats_v3() /
espn_wnba_player_stats_v3()
|
Season stats by category |
espn_wbb_player_gamelog() /
espn_wnba_player_gamelog()
|
Game-by-game log |
espn_wbb_player_splits() /
espn_wnba_player_splits()
|
Situational splits |
espn_wbb_player_eventlog() /
espn_wnba_player_eventlog()
|
Event log ($ref links) |
espn_wbb_player_awards() /
espn_wnba_player_awards()
|
Awards history |
espn_wbb_player_statisticslog() /
espn_wnba_player_statisticslog()
|
Stats log (core-v2) |
espn_wbb_player_stats() /
espn_wnba_player_stats()
|
Cross-athlete season stats |
Per-event enrichment
These take an event_id and complement the
play-by-play.
| Function | Returns |
|---|---|
espn_wbb_game_odds() /
espn_wnba_game_odds()
|
Opening / closing lines (WNBA only – empty for WBB) |
espn_wbb_game_probabilities() /
espn_wnba_game_probabilities()
|
Win probability per play |
espn_wbb_game_officials() /
espn_wnba_game_officials()
|
Officials |
espn_wbb_game_broadcasts() /
espn_wnba_game_broadcasts()
|
Broadcast outlets |
League-wide catalogs
| Function | Returns |
|---|---|
espn_wbb_leaders() /
espn_wnba_leaders()
|
League statistical leaders |
espn_wbb_venues() /
espn_wnba_venues()
|
Arenas |
espn_wbb_coaches() /
espn_wnba_coaches()
|
Coaches |
espn_wbb_athletes_index() /
espn_wnba_athletes_index()
|
Full athlete index |
espn_wbb_seasons() /
espn_wnba_seasons()
|
Seasons on record |
espn_wbb_season_info() /
espn_wnba_season_info()
|
Single-season metadata |
WNBA-only
The pro-league side has draft, free agency, and transaction logs that don’t have NCAA equivalents.
| Function | Returns |
|---|---|
espn_wnba_draft() |
Draft picks by season |
espn_wnba_freeagents() |
Free agents (during the FA window) |
espn_wnba_transactions() |
Transactions log |
Worked examples
The examples below use UConn (team_id = 2509) for WBB
and the Las Vegas Aces (team_id = 17) for the WNBA. Most
ESPN team IDs and athlete IDs are easy to discover with
espn_wbb_teams() / espn_wnba_teams() and the
various roster endpoints.
Browsing news and the season calendar
When you’re starting a new analysis, the easiest way to confirm the season is active and you’re hitting current data is to pull the news feed and the calendar.
library(wehoop)
# Latest 10 WBB news items
wbb_news <- espn_wbb_news(limit = 10)
head(wbb_news[, c("headline", "published")])
#> # A tibble: 6 × 2
#> headline published
#> <chr> <chr>
#> 1 Arizona's Burke calls out critics of post on wife's pregnancy 2026-06-…
#> 2 SEC's Sankey: Idea of super league 'not consistent with the truth' 2026-06-…
#> 3 NCAA panel tweaks D-I eligibility plan, could vote on it in late Ju… 2026-06-…
#> 4 Virginia Tech receives historic $75M donation, mostly for athletics 2026-06-…
#> 5 Nick Saban asks Congress to 'bring order' via college sports bill 2026-06-…
#> 6 SEC, Big Ten withhold support for landmark college sports bill 2026-06-…
# 2025 WBB season calendar
wbb_cal <- espn_wbb_calendar(season = 2025)
head(wbb_cal)
#> # A tibble: 6 × 12
#> season season_type season_type_label season_start_date season_end_date
#> <chr> <chr> <chr> <chr> <chr>
#> 1 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> 2 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> 3 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> 4 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> 5 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> 6 2025 NA NA 2024-07-13T07:00Z 2025-04-09T06:59Z
#> # ℹ 7 more variables: calendar_type <chr>, label <chr>, alternate_label <chr>,
#> # detail <chr>, value <chr>, start_date <chr>, end_date <chr>
# Same on the WNBA side
wnba_news <- espn_wnba_news(limit = 10)
wnba_cal <- espn_wnba_calendar(season = 2025)The calendar tibble carries one row per scheduling block (preseason, regular season, postseason, championship weeks, etc.), with start and end dates. It’s useful for filtering schedules and scoreboards down to a specific portion of the year.
Looking at a team
espn_wbb_team() and espn_wnba_team() return
a small named list with high-level identity, record, next event, and
coaching info. Pair it with the roster, schedule, and team-leader
wrappers when you want a fuller picture.
# UConn at a glance
uconn <- espn_wbb_team(team_id = 2509, season = 2025)
names(uconn) # Info, Record, NextEvent, StandingSummary, Coaches
#> [1] "Info" "Record" "NextEvent" "StandingSummary"
#> [5] "Coaches"
# Current roster
uconn_roster <- espn_wbb_team_roster(team_id = 2509, season = 2025)
head(uconn_roster[, c("athlete_display_name", "position_name", "jersey")])
#> Error in `uconn_roster[, c("athlete_display_name", "position_name", "jersey")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `athlete_display_name` doesn't exist.
# Regular-season schedule
uconn_sched <- espn_wbb_team_schedule(
team_id = 2509, season = 2025, season_type = 2
)
head(uconn_sched[, c("name", "date", "home_away", "score")])
#> Error in `uconn_sched[, c("name", "date", "home_away", "score")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `score` doesn't exist.
# Statistical leaders for the team
uconn_ldrs <- espn_wbb_team_leaders(team_id = 2509, season = 2025)
head(uconn_ldrs)
#> # A tibble: 0 × 0The same shape applies to WNBA teams –
espn_wnba_team(17, 2025) for the Aces, plus
_team_roster(), _team_schedule(), and so
on.
A small caveat on the roster and leaders endpoints: ESPN serves only
the current roster and leaders for each team, regardless of any
season you pass. The argument is preserved in the function
signature for API symmetry, but it doesn’t change the request URL.
Tracking injuries
Injury data is a soft spot in ESPN’s WBB coverage – most college games don’t carry an active injury report. WNBA injuries are more reliably populated when the league is in season.
# Whole league
wnba_inj <- espn_wnba_injuries(season = 2025)
# Single team
aces_inj <- espn_wnba_team_injuries(team_id = 17)
# WBB injuries are sparse on ESPN -- an empty tibble is the normal case
wbb_inj <- espn_wbb_injuries(season = 2025)If you’re building a workflow that depends on injury data, gate
downstream code on nrow(...) > 0.
Following an athlete
The athlete endpoints are the deepest part of the surface. Pull a
roster, pick a player, and you have biographical data, season-level
totals, a per-game log, situational splits, and an awards history all
keyed off the same athlete_id.
library(dplyr)
uconn_roster <- espn_wbb_team_roster(team_id = 2509, season = 2025)
athlete_id <- uconn_roster$athlete_id[1]
athlete_name <- uconn_roster$athlete_display_name[1]
message("Selected: ", athlete_name, " (", athlete_id, ")")
# Bio and profile
bio <- espn_wbb_player_info(athlete_id = athlete_id)
glimpse(bio)
#> List of 6
#> $ Bio : wehop_dt [1 × 16] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> ..$ id : chr "5311737"
#> ..$ uid : chr "s:40~l:54~a:5311737"
#> ..$ guid : chr "e082d6da-e8f8-32d8-8085-45ea3bfc5eac"
#> ..$ first_name : chr "Carley"
#> ..$ last_name : chr "Barrett"
#> ..$ full_name : chr "Carley Barrett"
#> ..$ display_name : chr "Carley Barrett"
#> ..$ short_name : chr "C. Barrett"
#> ..$ height : num 67
#> ..$ display_height: chr "5' 7\""
#> ..$ jersey : chr "24"
#> ..$ active : logi TRUE
#> ..$ headshot_href : chr "https://a.espncdn.com/i/headshots/womens-college-basketball/players/full/5311737.png"
#> ..$ birth_city : chr "Lafayette"
#> ..$ birth_state : chr "IN"
#> ..$ birth_country : chr "USA"
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete Bio from ESPN.com"
#> $ Team : wehop_dt [1 × 1] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> ..$ x_ref: chr "http://sports.core.api.espn.com/v2/sports/basketball/leagues/womens-college-basketball/seasons/2026/teams/2509?"| __truncated__
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete Team from ESPN.com"
#> $ Position: wehop_dt [1 × 5] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> ..$ id : chr "3"
#> ..$ name : chr "Guard"
#> ..$ display_name: chr "Guard"
#> ..$ abbreviation: chr "G"
#> ..$ leaf : logi FALSE
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete Position from ESPN.com"
#> $ Status : wehop_dt [1 × 4] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> ..$ id : chr "1"
#> ..$ name : chr "Active"
#> ..$ type : chr "active"
#> ..$ abbreviation: chr "Active"
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete Status from ESPN.com"
#> $ College : wehop_dt [0 × 0] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> Named list()
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete College from ESPN.com"
#> $ Draft : wehop_dt [0 × 0] (S3: wehoop_data/tbl_df/tbl/data.table/data.frame)
#> Named list()
#> ..- attr(*, "wehoop_timestamp")= POSIXct[1:1], format: "2026-06-13 06:06:45"
#> ..- attr(*, "wehoop_type")= chr "ESPN WOMENS-COLLEGE-BASKETBALL Athlete Draft from ESPN.com"
# Season overview (web-common-v3)
overview <- espn_wbb_player_overview(
athlete_id = athlete_id, season = 2025
)
names(overview)
#> [1] "Statistics" "NextGame" "Last5Games" "Headlines"
#> [5] "FantasyOutlook"
# Game-by-game log
gamelog <- espn_wbb_player_gamelog(
athlete_id = athlete_id, season = 2025
)
head(gamelog[, c("game_date", "opponent", "points", "rebounds", "assists")])
#> Error in `gamelog[, c("game_date", "opponent", "points", "rebounds", "assists")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `game_date`, `opponent`, `points`, `rebounds`, and `assists` don't exist.
# Situational splits (home/away, by month, vs ranked, ...)
splits <- espn_wbb_player_splits(
athlete_id = athlete_id, season = 2025
)
head(splits)
#> # A tibble: 1 × 4
#> athlete_id season name display_name
#> <chr> <dbl> <chr> <chr>
#> 1 5311737 2025 split splitEverything above works the same on the WNBA side – swap
espn_wbb_* for espn_wnba_* and use a WNBA
athlete_id (A’ja Wilson is "3149391").
A few things to know about the athlete endpoints:
-
espn_*_athlete_eventlog()returns$refURL columns rather than parsed game stats. Reach forespn_*_athlete_gamelog()if you want per-game numbers in tibble form. -
espn_*_athlete_awards()is sparse. Many athletes have no ESPN-recorded awards, so an empty tibble is normal. - The web-common-v3 endpoints (
_athlete_overview,_athlete_stats,_athlete_gamelog,_athlete_splits) are less stable than the rest of the surface. Some seasons before roughly 2018 return HTTP 404, and not every athlete is in the index.
Charting win probability
The combination of _pbp() and
_event_probabilities() is the quickest way to chart a
game’s momentum. Event '401736171' below is a 2024 WNBA
regular-season game.
library(wehoop)
library(dplyr)
library(ggplot2)
game_id <- "401736171"
pbp <- espn_wnba_pbp(game_id = game_id)
probs <- espn_wnba_game_probabilities(event_id = game_id, limit = 200)
plot_data <- probs %>%
mutate(seq = as.integer(sequence_number)) %>%
arrange(seq)
ggplot(plot_data, aes(x = seq, y = as.numeric(home_win_percentage))) +
geom_line(color = "#221A4D", linewidth = 0.8) +
geom_hline(yintercept = 0.5, linetype = "dashed", color = "grey50") +
labs(
title = paste("Win probability --", game_id),
x = "Play sequence",
y = "Home team win probability"
) +
theme_minimal()
You can layer in scoring plays from pbp to label
momentum swings, or join _event_officials() and
_event_broadcasts() if you want contextual annotations.
# Pre-game odds (populated when ESPN carries lines)
odds <- espn_wnba_game_odds(event_id = game_id)
# Officials
officials <- espn_wnba_game_officials(event_id = game_id)
officials[, c("full_name", "position")]
#> Error in `officials[, c("full_name", "position")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `position` doesn't exist.
# Broadcast outlets
broadcasts <- espn_wnba_game_broadcasts(event_id = game_id)
broadcasts[, c("market", "names")]
#> Error in `broadcasts[, c("market", "names")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `market` doesn't exist.ESPN doesn’t carry betting lines for NCAA games, so
espn_wbb_game_odds() always returns an empty tibble. The
function exists for API symmetry; it’s not a bug. Win probabilities,
officials, and broadcasts are all populated for both leagues.
Working with the WNBA draft and transactions
The draft, free agency, and transaction logs only exist on the WNBA side – the NCAA doesn’t have a pro-style draft on ESPN, and the transfer portal isn’t part of ESPN’s basketball API.
# 2025 WNBA draft picks
draft_2025 <- espn_wnba_draft(season = 2025)
head(draft_2025[, c("pick", "round", "team_name", "athlete_display_name")])
#> Error in `draft_2025[, c("pick", "round", "team_name", "athlete_display_name")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `team_name` and `athlete_display_name` don't exist.
# Recent transactions (waivers, trades, signings)
txn <- espn_wnba_transactions(season = 2025, limit = 100)
head(txn[, c("date", "type", "athlete_display_name", "team_name")])
#> Error in `txn[, c("date", "type", "athlete_display_name", "team_name")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `athlete_display_name` and `team_name` don't exist.
# Free agents -- empty outside the FA window, which is roughly
# January through April each year
fa <- espn_wnba_freeagents(season = 2025)
nrow(fa)
#> [1] 0If you’re stitching together a roster history, the natural sequence
is draft -> free agents -> transactions, joined on
athlete_id.
Browsing league-wide catalogs
Sometimes you don’t have a specific team or athlete in mind – you want the league-wide leaderboard, every venue, every coach, or the full athlete index. The catalog endpoints cover that.
# Statistical leaders (points, rebounds, assists, ...)
wnba_ldrs <- espn_wnba_leaders(season = 2024, season_type = 2)
head(wnba_ldrs)
#> # A tibble: 6 × 11
#> season season_type category abbreviation athlete_id athlete_name team_id
#> <int> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2024 2 pointsPerGame PTS 3149391 NA 17
#> 2 2024 2 pointsPerGame PTS 3904577 NA 3
#> 3 2024 2 pointsPerGame PTS 2998938 NA 11
#> 4 2024 2 pointsPerGame PTS 2998928 NA 9
#> 5 2024 2 pointsPerGame PTS 3917450 NA 8
#> 6 2024 2 pointsPerGame PTS 2987869 NA 17
#> # ℹ 4 more variables: team_abbrev <chr>, value <dbl>, rank <int>,
#> # display_value <chr>
# Every WNBA arena ESPN tracks
wnba_venues <- espn_wnba_venues()
head(wnba_venues[, c("full_name", "city", "state", "capacity")])
#> Error in `wnba_venues[, c("full_name", "city", "state", "capacity")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `city` and `state` don't exist.
# Coaches (current season)
wbb_coaches <- espn_wbb_coaches(season = 2025)
head(wbb_coaches[, c("full_name", "team_name", "experience")])
#> Error in `wbb_coaches[, c("full_name", "team_name", "experience")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `team_name` doesn't exist.The athlete index is the largest of the catalog endpoints – expect
6,000+ rows for a recent WBB season. Pagination is handled internally,
but for exploratory pulls you’ll usually want a small
limit.
# WNBA -- a couple hundred active players
wnba_athletes <- espn_wnba_athletes_index(
season = 2025, active = TRUE, limit = 5000
)
nrow(wnba_athletes)
#> [1] 221
head(wnba_athletes[, c("display_name", "position_name", "team_name")])
#> Error in `wnba_athletes[, c("display_name", "position_name", "team_name")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `display_name`, `position_name`, and `team_name` don't exist.
# WBB -- cap at 50 rows just to peek; the default limit is 25,000
wbb_athletes <- espn_wbb_athletes_index(season = 2025, limit = 50)
head(wbb_athletes[, c("display_name", "position_name", "team_name")])
#> Error in `wbb_athletes[, c("display_name", "position_name", "team_name")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Columns `display_name`, `position_name`, and `team_name` don't exist.The seasons catalog is mostly handy when you want to know which years ESPN has on record before you start a multi-season pull.
wnba_seasons <- espn_wnba_seasons()
head(wnba_seasons[, c("year", "start_date", "end_date")])
#> Error in `wnba_seasons[, c("year", "start_date", "end_date")]`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `year` doesn't exist.
# Single-season metadata is mostly $ref URLs to sub-resources, so
# espn_*_seasons() is usually the more useful starting point
wnba_s2025 <- espn_wnba_season_info(season = 2025)Core-v2 deep expansion
The post-3.0.0 release adds another ~62 ESPN core-v2 wrappers to
espn_wnba_* + espn_wbb_*, bringing the total
ESPN basketball surface in wehoop to 180
functions. Everything here is shimmed over an internal
.espn_basketball_* helper so WNBA and WBB share parsing
logic and bug fixes propagate to both leagues at once.
Function overview
| Tier | Family | WNBA | WBB | What it gives you |
|---|---|---|---|---|
| 1 / 2A | athlete_career_stats |
✓ | ✓ | Long-format career stats (1 row per stat). Default fetches RS + post and binds. |
| 1 / 2A | athlete_seasons |
✓ | ✓ | Index of seasons an athlete played, with $refs to
season-scoped detail |
| 1 / 2A |
franchises / franchise
|
✓ | ✓ | League franchise index + per-franchise detail (stable across relocations) |
| 1 / 2A | futures |
✓ | — | Per-season betting futures markets in long format |
| 1 / 2A |
tournaments / tournament /
tournament_seasons
|
— | ✓ | NCAA tournament index + per-tournament detail + per-season list |
| 1 / 2A |
team_record / team_odds_records
|
— | — | (NBA/MBB only) |
| 1 / 2A |
team_season_profile /
team_season_roster
|
✓ | ✓ | Per-(team × season) profile and roster |
| 1 / 2A |
coach / coach_season
|
— / ✓ | ✓ / ✓ | Coach detail; coach-in-a-season |
| 1 / 2A | powerindex |
✓ | ✓ | Per-season power-index entries per team |
| 1 / 2A |
season_info / season_type /
season_types
|
✓ | ✓ | Season metadata (top-level + per-season-type) |
| 1 / 2A | season_leaders |
✓ | ✓ | Per-(season × season-type) leader board, long format. Defaults fetch RS + post. |
| 1 / 2A |
season_rankings / season_ranking
|
✓ | ✓ | Per-season poll/ranking indexes |
| 1 / 2A |
season_weeks / season_week
|
✓ | ✓ | Weeks within a season (week-based leagues) |
| 1 / 2A |
week_rankings / week_ranking
|
✓ | ✓ | Per-week ranking lookups |
| 1 / 2A |
season_groups / season_group /
season_group_children /
season_group_teams
|
✓ | ✓ | Conferences / divisions / D-I groups within a season |
| 1 / 2A |
season_awards / award
|
✓ | ✓ | Per-season awards index + per-award detail |
| 1 / 2A | draft_pick |
✓ | — | Single pick lookup |
| 2B.1 | athlete_eventlog_v2 |
✓ | ✓ | Per-(athlete × season) event log (core-v2; richer than the web-common-v3 variant) |
| 2B.1 |
draft_rounds / draft_athletes /
draft_status
|
✓ | — | Draft year completion: rounds, draftees, in-progress status |
| 2B.2 | event_situation |
✓ | ✓ | Live game situation: timeouts, fouls, bonus state, last play
$ref
|
| 2B.2 | event_predictor |
✓ | ✓ | Pre-game predictor stats (one row per team × stat) |
| 2B.2 | event_powerindex |
✓ | ✓ | Per-event power-index index. Sparse coverage. |
| 2B.2 | event_propbets |
✓ | ✓ | Per-(event × provider) prop-bet markets in long format |
| 2B.3 | event_competitor_linescores |
✓ | ✓ | Per-quarter scoring for one team in one event |
| 2B.3 | event_competitor_leaders |
✓ | ✓ | Top performers per team in long format |
| 2B.3 | event_competitor_roster |
✓ | ✓ | Game-day roster index — athlete ids + $refs |
| 2B.3 | event_competitor_statistics |
✓ | ✓ | Full team-game statistics in long format |
| 2B.3 | event_competitor_records |
✓ | ✓ | Team records as of the event (overall / home / away / conf / div) |
| 2D |
positions / position
|
✓ | ✓ | Position dictionary index + detail (id-by-league, not shared) |
| 2E.1 | event_player_box |
✓ | ✓ | Per-game player box score, long format |
| 2E.1 | event_competitor_roster_entry |
✓ | ✓ | Single roster row: starter / DNP / ejection / sub slot |
| 2E.1 | event_play |
✓ | ✓ | Single-play detail (sequence, period, clock, scoring flags, coords) |
| 2E.1 | event_play_personnel |
✓ | ✓ | Players on court at a specific play. Sparse coverage. |
| 2E.2 | event_competitor_score |
✓ | ✓ | Single-row final score (value, displayValue, winner, source) |
| 2E.2 | team_season_statistics |
✓ | ✓ | Full team-season stat sheet in long format, with league rank per stat |
| 2E.2 | season_draft |
✓ | — | Draft-year top-level metadata |
| 2F | event_official_detail |
✓ | ✓ | Per-official detail. URL uses crew order (1-indexed),
not the ESPN stable id. |
| 2F | team_record_detail |
✓ | ✓ | Per-record stat array in long format |
| 2F | coach_record |
— | ✓ | Coach career record by type (Total / Pre Season / Regular Season / Post Season) |
| 2F | tournament_season |
— | ✓ | Single tournament-year detail |
| 2F | draft_athlete_detail |
✓ | — | Rich single-row drafted-player record |
Dashes mark families that don’t apply at ESPN for that league (no WNBA tournament structure; no WBB futures market; no WNBA coach detail endpoint; no WBB league-wide draft).
Athlete career, contracts, splits, and event log
Beyond the gamelog and per-season stats wrappers we shipped in the initial ESPN batch, the core-v2 surface adds career-level rollups, season-by-season indexes, and a richer event log.
library(wehoop)
# Career stats — long format, one row per (stat_type x category x stat).
# Default `stat_type = c(0L, 1L)` fetches regular season + postseason and
# binds them so a single call gives you the player's full career sheet.
caitlin_career <- espn_wbb_player_career_stats(athlete_id = 4433404)
aja_career <- espn_wnba_player_career_stats(athlete_id = 3149391)
# Per-(athlete x season) event log -- core-v2 variant. Returns
# event_id + result + per-event stats in long format.
espn_wnba_player_eventlog_v2(athlete_id = 3149391, season = 2024)
#> # A tibble: 25 × 8
#> league athlete_id season event_id team_id played event_ref competition_ref
#> <chr> <chr> <int> <chr> <chr> <lgl> <chr> <chr>
#> 1 wnba 3149391 2024 401620220 17 TRUE http://spo… http://sports.…
#> 2 wnba 3149391 2024 401620228 17 TRUE http://spo… http://sports.…
#> 3 wnba 3149391 2024 401620235 17 TRUE http://spo… http://sports.…
#> 4 wnba 3149391 2024 401620244 17 TRUE http://spo… http://sports.…
#> 5 wnba 3149391 2024 401620254 17 TRUE http://spo… http://sports.…
#> 6 wnba 3149391 2024 401620257 17 TRUE http://spo… http://sports.…
#> 7 wnba 3149391 2024 401620269 17 TRUE http://spo… http://sports.…
#> 8 wnba 3149391 2024 401620274 17 TRUE http://spo… http://sports.…
#> 9 wnba 3149391 2024 401620282 17 TRUE http://spo… http://sports.…
#> 10 wnba 3149391 2024 401620285 17 TRUE http://spo… http://sports.…
#> # ℹ 15 more rows
# Index of seasons an athlete has on file (good for iterating).
espn_wnba_player_seasons(athlete_id = 3149391)
#> # A tibble: 9 × 4
#> league athlete_id season ref
#> <chr> <chr> <int> <chr>
#> 1 wnba 3149391 2026 http://sports.core.api.espn.com/v2/sports/basketball…
#> 2 wnba 3149391 2025 http://sports.core.api.espn.com/v2/sports/basketball…
#> 3 wnba 3149391 2024 http://sports.core.api.espn.com/v2/sports/basketball…
#> 4 wnba 3149391 2023 http://sports.core.api.espn.com/v2/sports/basketball…
#> 5 wnba 3149391 2022 http://sports.core.api.espn.com/v2/sports/basketball…
#> 6 wnba 3149391 2021 http://sports.core.api.espn.com/v2/sports/basketball…
#> 7 wnba 3149391 2020 http://sports.core.api.espn.com/v2/sports/basketball…
#> 8 wnba 3149391 2019 http://sports.core.api.espn.com/v2/sports/basketball…
#> 9 wnba 3149391 2018 http://sports.core.api.espn.com/v2/sports/basketball…Franchises, tournaments, and league dictionaries
# Franchise records are stable across relocations and rebrands.
espn_wnba_franchises()
#> # A tibble: 17 × 3
#> franchise_id ref league
#> <chr> <chr> <chr>
#> 1 3 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 2 5 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 3 6 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 4 8 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 5 9 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 6 11 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 7 14 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 8 16 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 9 17 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 10 18 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 11 19 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 12 20 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 13 17475 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 14 17476 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 15 129689 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 16 131935 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
#> 17 132052 http://sports.core.api.espn.com/v2/sports/basketball/lea… wnba
espn_wnba_franchise(franchise_id = 20) # one franchise
#> # A tibble: 1 × 16
#> id uid slug location name nickname abbreviation display_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 20 s:40~l:59~f:20 atlant… Atlanta Dream Dream ATL Atlanta Dre…
#> # ℹ 8 more variables: short_display_name <chr>, color <chr>, is_active <lgl>,
#> # league <chr>, logo <chr>, logo_dark <chr>, venue_ref <chr>, team_ref <chr>
# WBB-only: NCAA tournament index + detail + season list.
espn_wbb_tournaments()
#> # A tibble: 38 × 3
#> tournament_id ref league
#> <chr> <chr> <chr>
#> 1 3 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 2 1 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 3 39 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 4 2 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 5 4 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 6 5 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 7 6 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 8 7 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 9 8 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> 10 9 http://sports.core.api.espn.com/v2/sports/basketball/le… women…
#> # ℹ 28 more rows
espn_wbb_tournament(tournament_id = 22)
#> # A tibble: 1 × 4
#> tournament_id display_name seasons_ref league
#> <chr> <chr> <chr> <chr>
#> 1 22 NCAA Womens Final 4 Tournament http://sports.core.api.es… women…
espn_wbb_tournament_seasons(tournament_id = 22)
#> # A tibble: 24 × 4
#> league tournament_id season ref
#> <chr> <chr> <int> <chr>
#> 1 womens-college-basketball 22 2003 http://sports.core.api.espn.c…
#> 2 womens-college-basketball 22 2004 http://sports.core.api.espn.c…
#> 3 womens-college-basketball 22 2005 http://sports.core.api.espn.c…
#> 4 womens-college-basketball 22 2006 http://sports.core.api.espn.c…
#> 5 womens-college-basketball 22 2007 http://sports.core.api.espn.c…
#> 6 womens-college-basketball 22 2008 http://sports.core.api.espn.c…
#> 7 womens-college-basketball 22 2009 http://sports.core.api.espn.c…
#> 8 womens-college-basketball 22 2010 http://sports.core.api.espn.c…
#> 9 womens-college-basketball 22 2011 http://sports.core.api.espn.c…
#> 10 womens-college-basketball 22 2012 http://sports.core.api.espn.c…
#> # ℹ 14 more rows
# Position dictionary. Position ids are NOT shared across leagues --
# id 1 is "Point Guard" in WNBA but "Center" in WBB.
espn_wnba_positions()
#> # A tibble: 12 × 3
#> position_id ref league
#> <chr> <chr> <chr>
#> 1 0 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 2 1 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 3 2 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 4 3 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 5 4 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 6 5 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 7 6 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 8 7 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 9 8 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 10 9 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 11 74 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
#> 12 99 http://sports.core.api.espn.com/v2/sports/basketball/leag… wnba
espn_wnba_position(position_id = 1)
#> # A tibble: 1 × 7
#> position_id name display_name abbreviation leaf parent_ref league
#> <chr> <chr> <chr> <chr> <lgl> <chr> <chr>
#> 1 1 Point Guard Point Guard PG TRUE http://sports.… wnbaSeason metadata, rankings, awards
# Per-season-type leaders, long format. Default fetches RS + post.
espn_wnba_season_leaders(season = 2024)
#> # A tibble: 750 × 15
#> league season season_type category_name category_display category_short
#> <chr> <int> <int> <chr> <chr> <chr>
#> 1 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 2 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 3 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 4 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 5 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 6 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 7 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 8 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 9 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 10 wnba 2024 2 pointsPerGame Points Per Game PPG
#> # ℹ 740 more rows
#> # ℹ 9 more variables: category_abbrev <chr>, rank <int>, athlete_id <chr>,
#> # team_id <chr>, display_value <chr>, value <dbl>, rel <chr>,
#> # athlete_ref <chr>, team_ref <chr>
# Award index for a season + per-award detail.
aw <- espn_wnba_season_awards(season = 2024)
espn_wnba_award(award_id = aw$award_id[1])
#> data frame with 0 columns and 0 rows
# Season group structure (conferences / D-I groups) -- mostly relevant
# for WBB, which has a deep conference hierarchy.
espn_wbb_season_groups(season = 2024, season_type = 2)
#> # A tibble: 2 × 5
#> league season season_type group_id ref
#> <chr> <int> <int> <chr> <chr>
#> 1 womens-college-basketball 2024 2 50 http://sports.core.api.…
#> 2 womens-college-basketball 2024 2 51 http://sports.core.api.…
espn_wbb_season_group(group_id = 50, season = 2024, season_type = 2)
#> # A tibble: 1 × 15
#> league season season_type group_id uid name abbreviation short_name
#> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 womens-colleg… 2024 2 50 s:40… NCAA… NCAA Division I
#> # ℹ 7 more variables: midsize_name <chr>, is_conference <lgl>, slug <chr>,
#> # parent_ref <chr>, children_ref <chr>, teams_ref <chr>, standings_ref <chr>
espn_wbb_season_group_teams(group_id = 50, season = 2024, season_type = 2)
#> # A tibble: 200 × 6
#> league season season_type group_id team_id ref
#> <chr> <int> <int> <chr> <chr> <chr>
#> 1 womens-college-basketball 2024 2 50 2 http://sports.…
#> 2 womens-college-basketball 2024 2 50 5 http://sports.…
#> 3 womens-college-basketball 2024 2 50 6 http://sports.…
#> 4 womens-college-basketball 2024 2 50 8 http://sports.…
#> 5 womens-college-basketball 2024 2 50 9 http://sports.…
#> 6 womens-college-basketball 2024 2 50 12 http://sports.…
#> 7 womens-college-basketball 2024 2 50 13 http://sports.…
#> 8 womens-college-basketball 2024 2 50 16 http://sports.…
#> 9 womens-college-basketball 2024 2 50 21 http://sports.…
#> 10 womens-college-basketball 2024 2 50 23 http://sports.…
#> # ℹ 190 more rowsTeam season profile, roster, and stats
# Per-(team x season) profile — a $ref index for that team-season's
# deeper resources (record, statistics, leaders, roster, ...).
espn_wbb_team_season_profile(team_id = 2509, season = 2024)
#> # A tibble: 1 × 35
#> id guid uid slug location name nickname abbreviation display_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2509 2fe4080d-… s:40… purd… Purdue Boil… Purdue PUR Purdue Boil…
#> # ℹ 26 more variables: short_display_name <chr>, color <chr>,
#> # alternate_color <chr>, is_active <lgl>, is_all_star <lgl>, season <int>,
#> # logo <chr>, logo_dark <chr>, record_ref <chr>, venue_ref <chr>,
#> # groups_ref <chr>, ranks_ref <chr>, statistics_ref <chr>, leaders_ref <chr>,
#> # injuries_ref <chr>, notes_ref <chr>, against_the_spread_records_ref <chr>,
#> # awards_ref <chr>, franchise_ref <chr>, depth_charts_ref <chr>,
#> # events_ref <chr>, transactions_ref <chr>, coaches_ref <chr>, …
# Roster the same team carried for that season.
espn_wbb_team_season_roster(team_id = 2509, season = 2024)
#> # A tibble: 23 × 5
#> league team_id season athlete_id ref
#> <chr> <chr> <int> <chr> <chr>
#> 1 womens-college-basketball 2509 2024 19486 http://sports.core.api.e…
#> 2 womens-college-basketball 2509 2024 4595183 http://sports.core.api.e…
#> 3 womens-college-basketball 2509 2024 4398945 http://sports.core.api.e…
#> 4 womens-college-basketball 2509 2024 5107952 http://sports.core.api.e…
#> 5 womens-college-basketball 2509 2024 4419354 http://sports.core.api.e…
#> 6 womens-college-basketball 2509 2024 5108545 http://sports.core.api.e…
#> 7 womens-college-basketball 2509 2024 5175721 http://sports.core.api.e…
#> 8 womens-college-basketball 2509 2024 5175722 http://sports.core.api.e…
#> 9 womens-college-basketball 2509 2024 4433438 http://sports.core.api.e…
#> 10 womens-college-basketball 2509 2024 4899062 http://sports.core.api.e…
#> # ℹ 13 more rows
# Full team-season stat sheet in long format, with league rank embedded
# per stat. Smoke-tested at 109 rows x 13 cols for a single NBA team --
# WBB shapes are comparable.
espn_wbb_team_season_statistics(team_id = 2509, season = 2024,
season_type = 2)
#> # A tibble: 77 × 13
#> league season season_type team_id category_name category_display stat_name
#> <chr> <int> <int> <chr> <chr> <chr> <chr>
#> 1 womens-c… 2024 2 2509 defensive Defensive blocks
#> 2 womens-c… 2024 2 2509 defensive Defensive defensiv…
#> 3 womens-c… 2024 2 2509 defensive Defensive steals
#> 4 womens-c… 2024 2 2509 defensive Defensive turnover…
#> 5 womens-c… 2024 2 2509 defensive Defensive avgDefen…
#> 6 womens-c… 2024 2 2509 defensive Defensive avgBlocks
#> 7 womens-c… 2024 2 2509 defensive Defensive avgSteals
#> 8 womens-c… 2024 2 2509 general General disquali…
#> 9 womens-c… 2024 2 2509 general General flagrant…
#> 10 womens-c… 2024 2 2509 general General fouls
#> # ℹ 67 more rows
#> # ℹ 6 more variables: stat_abbrev <chr>, stat_display <chr>, value <dbl>,
#> # display_value <chr>, rank <int>, rank_display_value <chr>Coach detail, coach-in-season, and coach career record
# Coach detail (single-row). Wnba has no coach wrapper at ESPN.
espn_wbb_coach(coach_id = 2167842)
#> # A tibble: 1 × 12
#> coach_id uid first_name last_name date_of_birth birth_city birth_state
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2167842 s:40~l:54~… Larry Vickers NA Virginia … VA
#> # ℹ 5 more variables: n_career_records <int>, n_coach_seasons <int>,
#> # college_ref <chr>, team_ref <chr>, league <chr>
# Coach-in-a-season: per-season stats and record.
espn_wbb_coach_season(coach_id = 2167842, season = 2024)
#> # A tibble: 1 × 13
#> league season coach_id uid first_name last_name date_of_birth birth_city
#> <chr> <int> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 womens-co… 2024 2167842 s:40… Larry Vickers NA Virginia …
#> # ℹ 5 more variables: birth_state <chr>, n_records <int>, person_ref <chr>,
#> # college_ref <chr>, team_ref <chr>
# Career record by type. Type codes: 0 = Total, 1 = Pre Season,
# 2 = Regular Season, 3 = Post Season.
espn_wbb_coach_record(coach_id = 2167842, record_type = 2)
#> # A tibble: 5 × 12
#> league coach_id record_type_id record_name record_type record_summary
#> <chr> <chr> <int> <chr> <chr> <chr>
#> 1 womens-college… 2167842 2 Regular Se… Regular Se… 0-0-0
#> 2 womens-college… 2167842 2 Regular Se… Regular Se… 0-0-0
#> 3 womens-college… 2167842 2 Regular Se… Regular Se… 0-0-0
#> 4 womens-college… 2167842 2 Regular Se… Regular Se… 0-0-0
#> 5 womens-college… 2167842 2 Regular Se… Regular Se… 0-0-0
#> # ℹ 6 more variables: record_display <chr>, stat_name <chr>, stat_abbrev <chr>,
#> # stat_display <chr>, value <dbl>, stat_display_value <chr>Event meta: live situation, predictor, power index, prop bets
# All four take an event_id from espn_*_schedule() or any boxscore.
EID <- "401736171"
# Live game situation -- timeouts, fouls, bonus state, last play $ref.
espn_wnba_game_situation(event_id = EID)
#> # A tibble: 1 × 15
#> league event_id home_timeouts_current home_timeouts_remaining
#> <chr> <chr> <int> <int>
#> 1 wnba 401736171 2 0
#> # ℹ 11 more variables: away_timeouts_current <int>,
#> # away_timeouts_remaining <int>, home_team_fouls <int>,
#> # home_team_fouls_current <int>, home_fouls_to_give <int>,
#> # home_bonus_state <chr>, away_team_fouls <int>,
#> # away_team_fouls_current <int>, away_fouls_to_give <int>,
#> # away_bonus_state <chr>, last_play_ref <chr>
# Pre-game predictor -- one row per (team x stat). Empty for past games.
espn_wnba_game_predictor(event_id = EID)
#> # A tibble: 6 × 13
#> league event_id name short_name last_modified side team_id stat_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… home 17 matchupQ…
#> 2 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… home 17 teamPred…
#> 3 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… home 17 teamPred…
#> 4 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… away 6 matchupQ…
#> 5 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… away 6 teamPred…
#> 6 wnba 401736171 Los Angeles… LA @ LV 2025-06-15T1… away 6 teamPred…
#> # ℹ 5 more variables: stat_display <chr>, description <chr>, value <dbl>,
#> # display_value <chr>, team_ref <chr>
# Per-event power index. Coverage is sparse -- many events return zero.
espn_wnba_game_powerindex(event_id = EID)
#> # A tibble: 2 × 4
#> league event_id team_id ref
#> <chr> <chr> <chr> <chr>
#> 1 wnba 401736171 6 http://sports.core.api.espn.com/v2/sports/basketball…
#> 2 wnba 401736171 17 http://sports.core.api.espn.com/v2/sports/basketball…
# Prop bet markets per (event x provider). 58 = ESPN BET.
espn_wnba_game_propbets(event_id = EID, provider_id = 58)
#> NULLEvent competitor sub-resources
Five resource families under
events/{eid}/competitions/{cid}/competitors/{team_id}/,
each shimmed for WNBA + WBB. Pair team_id with
event_id from espn_wnba_schedule()$id (or the
team_id from any boxscore-style call).
EID <- "401736171"; TID <- 17 # team_id of one competitor
# Per-quarter scoring for one team in one event.
espn_wnba_game_team_linescores(event_id = EID, team_id = TID)
#> # A tibble: 8 × 7
#> league event_id team_id period value display_value source
#> <chr> <chr> <chr> <int> <dbl> <chr> <chr>
#> 1 wnba 401736171 17 1 17 17 1
#> 2 wnba 401736171 17 1 17 17 Basic/Manual
#> 3 wnba 401736171 17 2 24 24 1
#> 4 wnba 401736171 17 2 24 24 Basic/Manual
#> 5 wnba 401736171 17 3 24 24 1
#> 6 wnba 401736171 17 3 24 24 Basic/Manual
#> 7 wnba 401736171 17 4 24 24 1
#> 8 wnba 401736171 17 4 24 24 Basic/Manual
# Top performers per team in long format (category x rank).
espn_wnba_game_team_leaders(event_id = EID, team_id = TID)
#> # A tibble: 28 × 11
#> league event_id team_id category_name category_display category_abbrev rank
#> <chr> <chr> <chr> <chr> <chr> <chr> <int>
#> 1 wnba 401736171 17 points Points Pts 1
#> 2 wnba 401736171 17 points Points Pts 2
#> 3 wnba 401736171 17 points Points Pts 3
#> 4 wnba 401736171 17 points Points Pts 4
#> 5 wnba 401736171 17 points Points Pts 5
#> 6 wnba 401736171 17 points Points Pts 6
#> 7 wnba 401736171 17 assists Assists Ast 1
#> 8 wnba 401736171 17 assists Assists Ast 2
#> 9 wnba 401736171 17 assists Assists Ast 3
#> 10 wnba 401736171 17 assists Assists Ast 4
#> # ℹ 18 more rows
#> # ℹ 4 more variables: athlete_id <chr>, display_value <chr>, value <dbl>,
#> # athlete_ref <chr>
# Game-day roster index. Returns athlete ids + core-v2 $refs.
espn_wnba_game_team_roster(event_id = EID, team_id = TID)
#> # A tibble: 0 × 5
#> # ℹ 5 variables: league <chr>, event_id <chr>, team_id <chr>, athlete_id <chr>,
#> # ref <chr>
# Full team-game statistics in long format.
espn_wnba_game_team_statistics(event_id = EID, team_id = TID)
#> # A tibble: 99 × 10
#> league event_id team_id category_name category_display stat_name stat_abbrev
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 wnba 401736171 17 defensive Defensive blocks BLK
#> 2 wnba 401736171 17 defensive Defensive defensiv… DR
#> 3 wnba 401736171 17 defensive Defensive steals STL
#> 4 wnba 401736171 17 defensive Defensive turnover… Points Con…
#> 5 wnba 401736171 17 defensive Defensive avgDefen… DR
#> 6 wnba 401736171 17 defensive Defensive avgBlocks BLK
#> 7 wnba 401736171 17 defensive Defensive avgSteals STL
#> 8 wnba 401736171 17 defensive Defensive avg48Def… DR
#> 9 wnba 401736171 17 defensive Defensive avg48Blo… BLK
#> 10 wnba 401736171 17 defensive Defensive avg48Ste… STL
#> # ℹ 89 more rows
#> # ℹ 3 more variables: stat_display <chr>, value <dbl>, display_value <chr>
# Team records as of the event: overall / home / away / conf / div.
espn_wnba_game_team_records(event_id = EID, team_id = TID)
#> # A tibble: 3 × 11
#> league event_id team_id record_id name abbreviation display_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 wnba 401736171 17 900 overall Game Record Year To Date
#> 2 wnba 401736171 17 33 Home NA Home
#> 3 wnba 401736171 17 34 Road NA Road
#> # ℹ 4 more variables: short_display_name <chr>, type <chr>, summary <chr>,
#> # value <dbl>
# One-row final score, quick lookup.
espn_wnba_game_team_score(event_id = EID, team_id = TID)
#> # A tibble: 1 × 8
#> league event_id team_id value display_value winner source_id
#> <chr> <chr> <chr> <dbl> <chr> <lgl> <chr>
#> 1 wnba 401736171 17 89 89 FALSE 1
#> # ℹ 1 more variable: source_description <chr>Per-game player box score, play detail, and on-court lineups
This is the headline 2E.1 batch – the per-(game x player) box score in long format plus single-play deep dives.
EID <- "401736171"; TID <- 17; AID <- 3149391 # event, team, athlete
# Per-game box score for one athlete -- one row per (category x stat).
# Same shape as event_competitor_statistics() but scoped to an athlete.
espn_wnba_game_player_box(event_id = EID, team_id = TID,
athlete_id = AID)
#> # A tibble: 97 × 12
#> league event_id team_id athlete_id stat_type category_name category_display
#> <chr> <chr> <chr> <chr> <int> <chr> <chr>
#> 1 wnba 401736171 17 3149391 0 defensive Defensive
#> 2 wnba 401736171 17 3149391 0 defensive Defensive
#> 3 wnba 401736171 17 3149391 0 defensive Defensive
#> 4 wnba 401736171 17 3149391 0 defensive Defensive
#> 5 wnba 401736171 17 3149391 0 defensive Defensive
#> 6 wnba 401736171 17 3149391 0 defensive Defensive
#> 7 wnba 401736171 17 3149391 0 defensive Defensive
#> 8 wnba 401736171 17 3149391 0 defensive Defensive
#> 9 wnba 401736171 17 3149391 0 defensive Defensive
#> 10 wnba 401736171 17 3149391 0 general General
#> # ℹ 87 more rows
#> # ℹ 5 more variables: stat_name <chr>, stat_abbrev <chr>, stat_display <chr>,
#> # value <dbl>, display_value <chr>
# Per-athlete game-day row: starter flag, did_not_play + reason,
# ejected flag, period of entry, for_player_id (substitution slot).
espn_wnba_game_team_roster_entry(event_id = EID, team_id = TID,
athlete_id = AID)
#> # A tibble: 1 × 16
#> league event_id team_id athlete_id player_id period active starter
#> <chr> <chr> <chr> <chr> <chr> <int> <lgl> <lgl>
#> 1 wnba 401736171 17 3149391 3149391 0 FALSE TRUE
#> # ℹ 8 more variables: did_not_play <lgl>, reason <chr>, ejected <lgl>,
#> # for_player_id <chr>, jersey <chr>, display_name <chr>, athlete_ref <chr>,
#> # position_ref <chr>
# Single-play detail. play_id comes from espn_wnba_pbp() output.
PID <- "401736171001" # example play id
espn_wnba_game_play(event_id = EID, play_id = PID)
#> NULL
# Players on court at a specific play (long format). Coverage is
# sparse -- many plays return zero rows.
espn_wnba_game_play_personnel(event_id = EID, play_id = PID)
#> NULLOfficials, team records, and the draft
# Single official detail. The URL segment is the CREW ORDER, not the
# ESPN-stable official_id -- so pair this with the `order` column from
# espn_wnba_game_officials() rather than `official_id`.
espn_wnba_game_official_detail(event_id = "401736171", order = 1)
#> # A tibble: 1 × 10
#> league event_id official_id first_name last_name full_name display_name
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 wnba 401736171 7671 Michael Price Michael Price Michael Price
#> # ℹ 3 more variables: position_id <chr>, position_name <chr>, order <int>
# Per-record stat array. Use espn_wnba_team_record() to discover
# valid record_id values for a (team_id, season) pair.
espn_wnba_team_record_detail(team_id = 17, season = 2024, record_id = 0)
#> # A tibble: 21 × 15
#> league team_id season season_type record_id record_name record_abbrev
#> <chr> <chr> <int> <int> <chr> <chr> <chr>
#> 1 wnba 17 2024 2 0 overall Total
#> 2 wnba 17 2024 2 0 overall Total
#> 3 wnba 17 2024 2 0 overall Total
#> 4 wnba 17 2024 2 0 overall Total
#> 5 wnba 17 2024 2 0 overall Total
#> 6 wnba 17 2024 2 0 overall Total
#> 7 wnba 17 2024 2 0 overall Total
#> 8 wnba 17 2024 2 0 overall Total
#> 9 wnba 17 2024 2 0 overall Total
#> 10 wnba 17 2024 2 0 overall Total
#> # ℹ 11 more rows
#> # ℹ 8 more variables: record_display <chr>, record_type <chr>,
#> # record_summary <chr>, stat_name <chr>, stat_abbrev <chr>,
#> # stat_display <chr>, value <dbl>, stat_display_value <chr>
# Draft year top-level metadata + rich single-pick record.
espn_wnba_season_draft(season = 2024)
#> # A tibble: 1 × 10
#> league season year uid number_of_rounds display_name short_display_name
#> <chr> <int> <int> <chr> <int> <chr> <chr>
#> 1 wnba 2024 2024 s:40~l:5… 3 2024 Women'… 2024 WNBA Draft
#> # ℹ 3 more variables: status_ref <chr>, athletes_ref <chr>, rounds_ref <chr>
espn_wnba_draft_athlete_detail(season = 2024, athlete_id = 5170843)
#> NULLOne thing to know about default season types
Most of the new wrappers that take a season_type
parameter default to c(2L, 3L) (regular season +
postseason) and bind the two results into a single tibble keyed by a
season_type column. This is more useful than the strict
season_type = 2 default for end-of-season analysis, and
pass season_type = 2 to limit to regular season only.
# Regular season only.
espn_wnba_season_leaders(season = 2024, season_type = 2)
#> # A tibble: 375 × 15
#> league season season_type category_name category_display category_short
#> <chr> <int> <int> <chr> <chr> <chr>
#> 1 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 2 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 3 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 4 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 5 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 6 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 7 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 8 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 9 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 10 wnba 2024 2 pointsPerGame Points Per Game PPG
#> # ℹ 365 more rows
#> # ℹ 9 more variables: category_abbrev <chr>, rank <int>, athlete_id <chr>,
#> # team_id <chr>, display_value <chr>, value <dbl>, rel <chr>,
#> # athlete_ref <chr>, team_ref <chr>
# Default — RS + post, bound, keyed by season_type column.
espn_wnba_season_leaders(season = 2024)
#> # A tibble: 750 × 15
#> league season season_type category_name category_display category_short
#> <chr> <int> <int> <chr> <chr> <chr>
#> 1 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 2 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 3 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 4 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 5 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 6 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 7 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 8 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 9 wnba 2024 2 pointsPerGame Points Per Game PPG
#> 10 wnba 2024 2 pointsPerGame Points Per Game PPG
#> # ℹ 740 more rows
#> # ℹ 9 more variables: category_abbrev <chr>, rank <int>, athlete_id <chr>,
#> # team_id <chr>, display_value <chr>, value <dbl>, rel <chr>,
#> # athlete_ref <chr>, team_ref <chr>What’s not here
A few endpoints exist on ESPN but are deliberately not wrapped:
| Endpoint | Why we skip it |
|---|---|
/teams/{id}/depth-charts |
ESPN basketball doesn’t carry depth charts |
cdn.espn.com/core game summary |
Fully redundant with espn_*_game_all()
|
core-v2 /events/{id}/plays
|
Strict downgrade of espn_*_pbp(); needs per-play
$ref resolution and returns less data |
espn_wnba_rankings (would-be) |
The WNBA has no poll; only WBB has
espn_wbb_rankings()
|
| WBB transfer portal | Not on ESPN’s basketball API |
And a handful of endpoints we do wrap that have known data quirks:
-
espn_wbb_injuries()andespn_wbb_team_injuries()– ESPN rarely populates injury data for college basketball. -
espn_wbb_game_odds()– always empty; ESPN doesn’t carry NCAA lines. -
espn_wnba_freeagents()– empty outside the FA window. -
espn_*_athlete_awards()– sparse for most athletes. -
espn_*_athlete_eventlog()– returns$refURLs, not parsed stats. Use_athlete_gamelog()instead. -
espn_*_season_info()– mostly$refURLs. - web-common-v3 endpoints – some legacy seasons return HTTP 404.
When something looks off, an empty tibble is far more often the
correct, expected return than a bug. ESPN’s basketball coverage is
uneven across leagues, seasons, and franchise tenures, and
wehoop mirrors that unevenness honestly rather than
papering over it.