draft.kings is an R package that wraps the undocumented DraftKings
API, providing seamless access to data and additional tools for fantasy
sports strategy.
Key features:
- Retrieve contests and draftable players
- List participants and scores
- Optimize lineups
draft.kings aims to be the most comprehensive API wrapper package for
DraftKings in any programming language. Users are encouraged to create
issues for new endpoints or bugs to help improve the package.
You can install the development version of draft.kings from GitHub with:
# install.packages("devtools")
devtools::install_github("gacolitti/draft.kings")Contest Info
contest_info <- dk_get_contest_info(contest_key = 133645678)
contest_info$contest_summary
#> [1] "This 215-player contest features $5,000.00 in total prizes and pays out the top 5 finishing positions. First place wins $1,000.00."
contest_info |>
dplyr::select(contest_key, contest_summary, payout_description, sport, entry_fee, entries)
#> # A tibble: 1 × 6
#> contest_key contest_summary payout_description sport entry_fee entries
#> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 133645678 This 215-player contes… $5,000 NFL 27 215Draft Group
draft_group <- dk_get_draft_group(draft_group_id = 75284)
draft_group |>
dplyr::select(draftable_id, player_id, first_name, last_name, position, salary, status)
#> # A tibble: 106 × 7
#> draftable_id player_id first_name last_name position salary status
#> <dbl> <dbl> <chr> <chr> <chr> <dbl> <chr>
#> 1 24633208 877745 Lamar Jackson QB 18300 None
#> 2 24633209 1109979 Ja'Marr Chase WR 16500 None
#> 3 24633210 878785 Joe Burrow QB 15900 None
#> 4 24633211 820699 Mark Andrews TE 14400 None
#> 5 24633212 820727 Joe Mixon RB 13200 None
#> 6 24633213 978579 Tee Higgins WR 12300 None
#> 7 24633261 877745 Lamar Jackson QB 12200 None
#> 8 24633262 1109979 Ja'Marr Chase WR 11000 None
#> 9 24633263 878785 Joe Burrow QB 10600 None
#> 10 24633214 976513 J.K. Dobbins RB 10500 None
#> # ℹ 96 more rowsDraft Group Info
dg_info <- dk_get_draft_group_info(draft_group_id = 75284)
dg_info$info |>
dplyr::select(draft_group_id, game_type_id, sport, game_type, min_start_time, max_start_time)
#> # A tibble: 1 × 6
#> draft_group_id game_type_id sport game_type min_start_time max_start_time
#> <int> <int> <chr> <chr> <chr> <chr>
#> 1 75284 96 NFL SalaryCap 2022-10-10T00:20:0… 2022-10-10T00…
dg_info$games |>
dplyr::select(game_id, away_team_id, home_team_id, start_date, location, time_remaining_status)
#> # A tibble: 1 × 6
#> game_id away_team_id home_team_id start_date location time_remaining_status
#> <int> <int> <int> <chr> <chr> <chr>
#> 1 5819761 327 366 2022-10-10T0… M&T Ban… Final
dg_info$leagues |>
dplyr::select(league_id, league_name, league_abbreviation)
#> # A tibble: 1 × 3
#> league_id league_name league_abbreviation
#> <int> <chr> <chr>
#> 1 1 National Football League NFLLeaderboard
leaderboard <- dk_get_leaderboard(contest_key = 133645678)
leaderboard |>
dplyr::select(draft_group_id, contest_key, entry_key, user_name, rank, fantasy_points)
#> # A tibble: 215 × 6
#> draft_group_id contest_key entry_key user_name rank fantasy_points
#> <int> <chr> <chr> <chr> <int> <dbl>
#> 1 75284 133645678 3412356478 GenoMike21 1 101.
#> 2 75284 133645678 3416201807 carlitosway9 1 101.
#> 3 75284 133645678 3416313295 KidRaider3 1 101.
#> 4 75284 133645678 3416410911 carlosking89 4 97.6
#> 5 75284 133645678 3416034618 sjamo35 5 96.3
#> 6 75284 133645678 3416642033 Jace2013 6 96.2
#> 7 75284 133645678 3416680035 Bucknutz00 7 94.2
#> 8 75284 133645678 3415573084 JWolff33 8 93.9
#> 9 75284 133645678 3416580244 eracnrobert 9 90.2
#> 10 75284 133645678 3415480406 Maria2199 10 90.1
#> # ℹ 205 more rowsEntries
entries <- dk_get_entries(draft_group_id = 80584, entry_keys = c(3618408508, 3618897002))
entries |>
dplyr::select(entry_key, draftable_id, display_name, roster_position, fantasy_points)
#> # A tibble: 76 × 5
#> entry_key draftable_id display_name roster_position fantasy_points
#> <chr> <int> <chr> <chr> <dbl>
#> 1 3618408508 26369002 Cole Beasley FLEX 6
#> 2 3618408508 26369002 Cole Beasley FLEX 3.5
#> 3 3618408508 26369002 Cole Beasley FLEX 2
#> 4 3618408508 26369002 Cole Beasley FLEX 0
#> 5 3618408508 26369002 Cole Beasley FLEX 0
#> 6 3618408508 26368984 Gabe Davis FLEX 6
#> 7 3618408508 26368984 Gabe Davis FLEX 11.3
#> 8 3618408508 26368984 Gabe Davis FLEX 6
#> 9 3618408508 26368984 Gabe Davis FLEX 3
#> 10 3618408508 26368984 Gabe Davis FLEX 0
#> # ℹ 66 more rowsPrepare Schematic
# prepare schematic with contest rules and DraftKings player projections
schematic <- dk_prepare_schematic(draft_group_id = 80584)
schematic |> names()
#> [1] "draft_group" "rules" "draft_group_id"Run Optimization
# perform lineup optimization based on rules and player projections
optimized_lineup <- dk_optimize_lineup(schematic)Extract Solution
# extract solution from optimized lineup object
solution <- dk_extract_solution(optimized_lineup)
solution |> names()
#> [1] "optimal_lineup" "draft_group_id" "salary_total" "exp_fp_total"
# exp_fp is the expected fantasy points for each player in the lineup
solution$optimal_lineup |>
dplyr::select(draftable_id, display_name, position, salary, exp_fp)
#> draftable_id display_name position salary exp_fp
#> 1 26368922 Josh Allen QB 18600 39.0
#> 2 26368976 Tyreek Hill WR 11000 24.6
#> 3 26368982 Raheem Mostert RB 8000 17.4
#> 4 26368990 James Cook RB 5400 14.1
#> 5 26368996 Jason Sanders K 3800 8.2
#> 6 26368997 Dolphins DST 3200 8.6
# total expected fantasy points for the lineup
solution$exp_fp_total
#> [1] 111.9