This function returns a tidy dataframe of common league settings, including details like "1QB" or "2QB/SF", scoring, best ball, team count, IDP etc. This is potentially useful in summarising the features of multiple leagues.
ff_league(conn) # S3 method for flea_conn ff_league(conn) # S3 method for mfl_conn ff_league(conn) # S3 method for sleeper_conn ff_league(conn)
| conn | the connection object created by |
|---|
A one-row summary of each league's main features.
flea_conn: Flea: returns a summary of league features.
mfl_conn: MFL: returns a summary of league features.
sleeper_conn: Sleeper: returns a summary of league features.
#> # A tibble: 1 x 14 #> league_id league_name league_type franchise_count qb_type idp scoring_flags #> <chr> <chr> <chr> <dbl> <chr> <lgl> <chr> #> 1 206154 Jackpot Dy… dynasty 16 1QB TRUE 0.5_ppr, TEP… #> # … with 7 more variables: best_ball <lgl>, salary_cap <lgl>, #> # player_copies <dbl>, qb_count <chr>, roster_size <int>, league_depth <dbl>, #> # keeper_count <int># } # \donttest{ ssb_conn <- ff_connect(platform = "mfl", league_id = 54040, season = 2020) ff_league(ssb_conn)#> # A tibble: 1 x 13 #> league_id league_name franchise_count qb_type idp scoring_flags best_ball #> <chr> <chr> <dbl> <chr> <lgl> <chr> <lgl> #> 1 54040 The Super … 14 1QB FALSE 0.5_ppr, TEP… TRUE #> # … with 6 more variables: salary_cap <lgl>, player_copies <dbl>, #> # years_active <chr>, qb_count <chr>, roster_size <dbl>, league_depth <dbl># } jml_conn <- ff_connect(platform = "sleeper", league_id = "522458773317046272", season = 2020) ff_league(jml_conn)#> # A tibble: 1 x 15 #> league_id league_name league_type franchise_count qb_type idp scoring_flags #> <chr> <chr> <chr> <dbl> <chr> <lgl> <chr> #> 1 52245877… The JanMic… dynasty 12 1QB FALSE 0.5_ppr #> # … with 8 more variables: best_ball <lgl>, salary_cap <lgl>, #> # player_copies <dbl>, years_active <chr>, qb_count <chr>, roster_size <int>, #> # league_depth <dbl>, prev_league_ids <chr>