ff_scoring {ffscrapr} | R Documentation |
Get League Scoring Settings
Description
This function returns a dataframe with detailed scoring settings for each league - broken down by event, points, and (if available) position.
Usage
ff_scoring(conn)
## S3 method for class 'espn_conn'
ff_scoring(conn)
## S3 method for class 'flea_conn'
ff_scoring(conn)
## S3 method for class 'mfl_conn'
ff_scoring(conn)
## S3 method for class 'sleeper_conn'
ff_scoring(conn)
## S3 method for class 'template_conn'
ff_scoring(conn)
Arguments
conn |
a conn object created by |
Value
A tibble of league scoring rules for each position defined.
Methods (by class)
-
ff_scoring(espn_conn)
: ESPN: returns scoring settings in a flat table, override positions have their own scoring. -
ff_scoring(flea_conn)
: Fleaflicker: returns scoring settings in a flat table, one row per position per rule. -
ff_scoring(mfl_conn)
: MFL: returns scoring settings in a flat table, one row per position per rule. -
ff_scoring(sleeper_conn)
: Sleeper: returns scoring settings in a flat table, one row per position per rule. -
ff_scoring(template_conn)
: Template: returns MFL style scoring settings in a flat table, one row per position per rule.
See Also
http://www03.myfantasyleague.com/2020/scoring_rules#rules
Examples
try({ # try only shown here because sometimes CRAN checks are weird
conn <- espn_connect(season = 2020, league_id = 899513)
ff_scoring(conn)
}) # end try
try({ # try only shown here because sometimes CRAN checks are weird
joe_conn <- ff_connect(platform = "fleaflicker", league_id = 312861, season = 2020)
ff_scoring(joe_conn)
}) # end try
try({ # try only shown here because sometimes CRAN checks are weird
ssb_conn <- ff_connect(platform = "mfl", league_id = 54040, season = 2020)
ff_scoring(ssb_conn)
}) # end try
try({ # try only shown here because sometimes CRAN checks are weird
jml_conn <- ff_connect(platform = "sleeper", league_id = "522458773317046272", season = 2020)
ff_scoring(jml_conn)
}) # end try
template_ppr <- ff_template(scoring_type = "ppr")
ff_scoring(template_ppr)