This function returns a tidy dataframe of player scores based on league rules.

Unfortunately, Sleeper has deprecated their player stats endpoint from their supported/open API. Please see ff_scoringhistory() for an alternative reconstruction.

ff_playerscores(conn, ...)

# S3 method for espn_conn
ff_playerscores(conn, limit = 1000, ...)

# S3 method for flea_conn
ff_playerscores(conn, page_limit = NULL, ...)

# S3 method for mfl_conn
ff_playerscores(conn, season, week, ...)

# S3 method for sleeper_conn
ff_playerscores(conn, ...)

Arguments

conn

the list object created by ff_connect()

...

other arguments (currently unused)

limit

A numeric describing the number of players to return - default 1000

page_limit

A numeric describing the number of pages to return - default NULL returns all available

season

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

week

a numeric vector (ie 1:17) or one of YTD (year-to-date) or AVG (average to date)

Value

A tibble of historical player scoring

Methods (by class)

  • espn_conn: ESPN: returns total points for season and average per game, for both current and previous season.

  • flea_conn: Fleaflicker: returns the season, season average, and standard deviation

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

  • sleeper_conn: Sleeper: Deprecated their open API endpoint for player scores

See also

ff_scoringhistory

Examples

# \donttest{ try({ # try only shown here because sometimes CRAN checks are weird conn <- espn_connect(season = 2020, league_id = 899513) ff_playerscores(conn, limit = 5) }) # end try
#> # A tibble: 5 × 8 #> season player_id player_name pos score_total score_average franchise_id #> <int> <int> <chr> <chr> <dbl> <dbl> <int> #> 1 2020 3054850 Alvin Kamara RB 337. 22.5 9 #> 2 2020 3043078 Derrick Henry RB 324. 20.2 4 #> 3 2020 16800 Davante Adams WR 301. 21.5 2 #> 4 2020 15795 DeAndre Hopkins WR 230. 14.4 4 #> 5 2020 2576925 Darren Waller TE 225. 14.1 4 #> # … with 1 more variable: franchise_name <chr>
# } # \donttest{ try({ # try only shown here because sometimes CRAN checks are weird conn <- fleaflicker_connect(2020, 312861) ff_playerscores(conn, page_limit = 2) }) # end try
#> # A tibble: 60 × 8 #> player_id player_name pos team games score_total score_avg score_sd #> <int> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 13761 Josh Allen QB BUF 16 550. 34.4 10.4 #> 2 3452 Aaron Rodgers QB GB 16 542. 33.8 8.49 #> 3 12894 Patrick Mahomes QB KC 15 520. 34.6 9.95 #> 4 8598 Russell Wilson QB SEA 16 513. 32.1 10.8 #> 5 14664 Kyler Murray QB ARI 16 507. 31.7 11.9 #> 6 12919 Deshaun Watson QB HOU 16 503. 31.5 7.96 #> 7 309 Tom Brady QB TB 16 488. 30.5 12.2 #> 8 8514 Ryan Tannehill QB TEN 16 469. 29.3 9.76 #> 9 15516 Justin Herbert QB LAC 15 459. 30.6 9.67 #> 10 8625 Kirk Cousins QB MIN 16 446. 27.9 9.8 #> # … with 50 more rows
# } # \donttest{ try({ # try only shown here because sometimes CRAN checks are weird sfb_conn <- mfl_connect(2020, league_id = 65443) ff_playerscores(conn = sfb_conn, season = 2019, week = "YTD") }) # end try
#> # A tibble: 589 × 8 #> season week player_id player_name pos team points is_available #> <dbl> <chr> <chr> <chr> <chr> <chr> <dbl> <chr> #> 1 2019 YTD 13593 Jackson, Lamar QB BAL 489. 1 #> 2 2019 YTD 13130 McCaffrey, Christian RB CAR 447. 1 #> 3 2019 YTD 12652 Thomas, Michael WR NOS 338. 1 #> 4 2019 YTD 13113 Watson, Deshaun QB HOU 330. 1 #> 5 2019 YTD 11244 Kelce, Travis TE KCC 317. 1 #> 6 2019 YTD 10703 Wilson, Russell QB SEA 315. 1 #> 7 2019 YTD 12620 Prescott, Dak QB DAL 314. 1 #> 8 2019 YTD 13128 Cook, Dalvin RB MIN 313. 1 #> 9 2019 YTD 13319 Jones, Aaron RB GBP 312 1 #> 10 2019 YTD 12625 Elliott, Ezekiel RB DAL 309. 1 #> # … with 579 more rows
# }