README.md

In fflr: Retrieve ESPN Fantasy Football Data

fflr

The fflr package is used to query the ESPN Fantasy Football API. Get data on fantasy football league members, teams, and individual athletes.

This package has been tested with a narrow subset of possible league settings. If a function doesn’t work as intended, please file an issue on GitHub.

Installation

You can install the release version of fflr from CRAN:

install.packages("fflr")

The most recent development version can be installed from GitHub:

# install.packages("remotes")
remotes::install_github("kiernann/fflr")

Usage

library(fflr)
packageVersion("fflr")
#> [1] '2.2.0'

Data is only available for public leagues. See this help page on how to make a private league public

Functions require a unique leagueId, which can be found in any ESPN page URL.

https://fantasy.espn.com/football/league?leagueId=42654852

Use ffl_id() to set a default fflr.leagueId option. Your .Rprofile file can set this option on startup.

ffl_id(leagueId = "42654852")
#> Temporarily set `fflr.leagueId` option to 42654852
#> [1] "42654852"

The leagueId argument defaults to ffl_id() and can be omitted once set.

league_info()
#> # A tibble: 1 × 6
#>         id seasonId name             isPublic  size finalScoringPeriod
#>      <int>    <int> <chr>            <lgl>    <int>              <int>
#> 1 42654852     2023 FFLR Test League TRUE         4                 17
league_teams()
#> # A tibble: 4 × 5
#>   abbrev teamId location nickname   memberId                              
#>   <fct>   <int> <chr>    <chr>      <chr>                                 
#> 1 AUS         1 Austin   Astronauts {22DFE7FF-9DF2-4F3B-9FE7-FF9DF2AF3BD2}
#> 2 BOS         2 Boston   Buzzards   {22DFE7FF-9DF2-4F3B-9FE7-FF9DF2AF3BD2}
#> 3 CHI         3 Chicago  Crowns     {22DFE7FF-9DF2-4F3B-9FE7-FF9DF2AF3BD2}
#> 4 DEN         4 Denver   Devils     {22DFE7FF-9DF2-4F3B-9FE7-FF9DF2AF3BD2}

The scoringPeriodId argument can be used to get data from past weeks.

all_rost <- team_roster(scoringPeriodId = 1)
all_rost$CHI[, 5:13][-7]
#> # A tibble: 16 × 8
#>    lineupSlot playerId firstName lastName    proTeam position projectedScore actualScore
#>    <fct>         <int> <chr>     <chr>       <fct>   <fct>             <dbl>       <dbl>
#>  1 QB          4040715 Jalen     Hurts       Phi     QB                21.3        12.5 
#>  2 RB          3929630 Saquon    Barkley     NYG     RB                16.9         9.3 
#>  3 RB          4239996 Travis    Etienne Jr. Jax     RB                15.1        21.4 
#>  4 WR          4262921 Justin    Jefferson   Min     WR                20.1        24   
#>  5 WR          4569618 Garrett   Wilson      NYJ     WR                16.4        14.4 
#>  6 TE            15847 Travis    Kelce       KC      TE                 0           0   
#>  7 FLEX        4374302 Amon-Ra   St. Brown   Det     WR                16.7        19.1 
#>  8 D/ST         -16025 49ers     D/ST        SF      D/ST               7.78       14   
#>  9 K           3055899 Harrison  Butker      KC      K                  8.41        8   
#> 10 BE          4429795 Jahmyr    Gibbs       Det     RB                14.0         8   
#> 11 BE          3042519 Aaron     Jones       GB      RB                15.5        26.7 
#> 12 BE          3915511 Joe       Burrow      Cin     QB                19.8         3.18
#> 13 BE          2976499 Amari     Cooper      Cle     WR                13.6         6.7 
#> 14 BE          4697815 Rachaad   White       TB      RB                13.9         6.9 
#> 15 BE          3054850 Alvin     Kamara      NO      RB                 0           0   
#> 16 BE          4038941 Justin    Herbert     LAC     QB                16.9        20.9

There are included objects for NFL teams and players.

nfl_teams
#> # A tibble: 33 × 6
#>    proTeamId abbrev location   name       byeWeek conference
#>        <int> <fct>  <chr>      <chr>        <int> <chr>     
#>  1         0 FA     <NA>       Free Agent      NA <NA>      
#>  2         1 Atl    Atlanta    Falcons         14 NFC       
#>  3         2 Buf    Buffalo    Bills            7 AFC       
#>  4         3 Chi    Chicago    Bears           14 NFC       
#>  5         4 Cin    Cincinnati Bengals         10 AFC       
#>  6         5 Cle    Cleveland  Browns           9 AFC       
#>  7         6 Dal    Dallas     Cowboys          9 NFC       
#>  8         7 Den    Denver     Broncos          9 AFC       
#>  9         8 Det    Detroit    Lions            6 NFC       
#> 10         9 GB     Green Bay  Packers         14 NFC       
#> # ℹ 23 more rows

The fflr project is released with a Contributor Code of Conduct. By contributing, you agree to abide by its terms.

fflr documentation built on Sept. 14, 2023, 9:10 a.m.