Get Starting Lineups

This function returns a tidy dataframe with one row for every starter (and bench) for every week and their scoring, if available.

Usage

ff_starters(conn, ...)

# S3 method for espn_conn
ff_starters(conn, weeks = 1:17, ...)

# S3 method for flea_conn
ff_starters(conn, week = 1:17, ...)

# S3 method for mfl_conn
ff_starters(conn, week = 1:17, season = NULL, ...)

# S3 method for sleeper_conn
ff_starters(conn, week = 1:17, ...)

Arguments

conn

the list object created by ff_connect()

...

other arguments (currently unused)

weeks

which weeks to calculate, a number or numeric vector

week

a numeric or one of YTD (year-to-date) or AVG (average to date)

season

the season of interest - generally only the most recent 2-3 seasons are available

Value

A tidy dataframe with every player for every week, including a flag for whether they were started or not

Methods (by class)

• espn_conn: ESPN: returns who was started as well as what they scored.

• flea_conn: Fleaflicker: returns who was started as well as what they scored.

• mfl_conn: MFL: returns the player fantasy scores for each week (not the actual stats)

• sleeper_conn: Sleeper: returns only "who" was started, without any scoring/stats data. Only returns season specified in initial connection object.

Examples

# \donttest{
try({ # try only shown here because sometimes CRAN checks are weird
  conn <- espn_connect(season = 2020, league_id = 1178049)
  ff_starters(conn, weeks = 1:3)
}) # end try
#> # A tibble: 714 × 12
#>     week franchise_id franchise_name    franchise_score lineup_slot player_score
#>    <int>        <int> <chr>                       <dbl> <chr>              <dbl>
#>  1     1            1 Rushin' Collusion             118 QB                  27.5
#>  2     1            1 Rushin' Collusion             118 RB                   9.2
#>  3     1            1 Rushin' Collusion             118 RB                   6.7
#>  4     1            1 Rushin' Collusion             118 WR                  13.1
#>  5     1            1 Rushin' Collusion             118 WR                   8.6
#>  6     1            1 Rushin' Collusion             118 WR                  12.6
#>  7     1            1 Rushin' Collusion             118 TE                  16.6
#>  8     1            1 Rushin' Collusion             118 DST                  0  
#>  9     1            1 Rushin' Collusion             118 K                    9  
#> 10     1            1 Rushin' Collusion             118 BE                   4.8
#> # … with 704 more rows, and 6 more variables: projected_score <dbl>,
#> #   player_id <int>, player_name <chr>, pos <chr>, team <chr>,
#> #   eligible_lineup_slots <list>
# }

# \donttest{
try({ # try only shown here because sometimes CRAN checks are weird
  conn <- fleaflicker_connect(season = 2020, league_id = 206154)
  ff_starters(conn)
}) # end try
# }

# \donttest{
try({ # try only shown here because sometimes CRAN checks are weird
  dlf_conn <- mfl_connect(2020, league_id = 37920)
  ff_starters(conn = dlf_conn)
}) # end try
#> # A tibble: 6,371 × 11
#>    franchise_id franchise_name          season  week starter_status should_start
#>    <chr>        <chr>                    <dbl> <int> <chr>                 <dbl>
#>  1 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  2 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  3 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  4 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  5 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  6 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  7 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  8 0013         Advance Reptilian Sola…   2020     1 starter                   1
#>  9 0013         Advance Reptilian Sola…   2020     1 starter                   1
#> 10 0013         Advance Reptilian Sola…   2020     1 nonstarter                0
#> # … with 6,361 more rows, and 5 more variables: player_score <dbl>,
#> #   player_id <chr>, player_name <chr>, pos <chr>, team <chr>
# }

# \donttest{
try({ # try only shown here because sometimes CRAN checks are weird
  jml_conn <- sleeper_connect(league_id = "522458773317046272", season = 2020)
  ff_starters(jml_conn, week = 3)
}) # end try
#> # A tibble: 344 × 8
#>    franchise_id franchise_name  week starter_status player_id player_name  pos  
#>           <int> <chr>          <dbl> <chr>          <chr>     <chr>        <chr>
#>  1            1 Fake News          3 nonstarter     7082      Dalton Keene TE   
#>  2            1 Fake News          3 nonstarter     6826      Cole Kmet    TE   
#>  3            1 Fake News          3 nonstarter     6804      Jordan Love  QB   
#>  4            1 Fake News          3 nonstarter     676       LeSean McCoy RB   
#>  5            1 Fake News          3 nonstarter     6149      Darius Slay… WR   
#>  6            1 Fake News          3 nonstarter     6068      Devine Ozig… RB   
#>  7            1 Fake News          3 nonstarter     6001      Drew Sample  TE   
#>  8            1 Fake News          3 nonstarter     5965      Miles Boykin WR   
#>  9            1 Fake News          3 nonstarter     5068      Kerryon Joh… RB   
#> 10            1 Fake News          3 nonstarter     5022      Dallas Goed… TE   
#> # … with 334 more rows, and 1 more variable: team <chr>
# }