The backbone of the ffsimulator resampling process is coming up with a population of weekly outcomes for every preseason positional rank. This function creates that dataframe by connecting historical FantasyPros.com rankings to nflfastR-based scoring data, as created by ffscrapr::ff_scoringhistory().

ffs_adp_outcomes(
  scoring_history,
  gp_model = "simple",
  pos_filter = c("QB", "RB", "WR", "TE")
)

Arguments

scoring_history

a scoring history table as created by ffscrapr::ff_scoringhistory()

gp_model

either "simple" or "none" - simple uses the average games played per season for each position/adp combination, none assumes every game is played.

pos_filter

a character vector: filter the positions returned to these specific positions, default: c("QB","RB","WR","TE)

Value

a dataframe with position, rank, probability of games played, and a corresponding nested list per row of all week score outcomes.

See also

fp_rankings_history for the included historical rankings

fp_injury_table for the historical injury table

vignette("custom") for usage details.

Examples

# \donttest{ # cached data scoring_history <- .ffs_cache("mfl_scoring_history.rds") ffs_adp_outcomes(scoring_history, gp_model = "simple")
#> # A tidytable: 640 × 6 #> pos rank prob_gp week_outcomes player_name fantasypros_id #> <chr> <dbl> <dbl> <list> <list> <list> #> 1 QB 1 0.919 <dbl [88]> <chr [6]> <chr [6]> #> 2 QB 2 0.919 <dbl [80]> <chr [6]> <chr [6]> #> 3 QB 3 0.919 <dbl [83]> <chr [6]> <chr [6]> #> 4 QB 4 0.919 <dbl [84]> <chr [6]> <chr [6]> #> 5 QB 5 0.919 <dbl [95]> <chr [6]> <chr [6]> #> 6 QB 6 0.918 <dbl [81]> <chr [6]> <chr [6]> #> 7 QB 7 0.917 <dbl [82]> <chr [6]> <chr [6]> #> 8 QB 8 0.915 <dbl [78]> <chr [6]> <chr [6]> #> 9 QB 9 0.913 <dbl [83]> <chr [6]> <chr [6]> #> 10 QB 10 0.911 <dbl [83]> <chr [6]> <chr [6]> #> # … with 630 more rows
ffs_adp_outcomes(scoring_history, gp_model = "none")
#> # A tidytable: 644 × 6 #> pos rank prob_gp week_outcomes player_name fantasypros_id #> <chr> <dbl> <dbl> <list> <list> <list> #> 1 QB 1 1 <dbl [88]> <chr [6]> <chr [6]> #> 2 QB 2 1 <dbl [80]> <chr [6]> <chr [6]> #> 3 QB 3 1 <dbl [83]> <chr [6]> <chr [6]> #> 4 QB 4 1 <dbl [84]> <chr [6]> <chr [6]> #> 5 QB 5 1 <dbl [95]> <chr [6]> <chr [6]> #> 6 QB 6 1 <dbl [81]> <chr [6]> <chr [6]> #> 7 QB 7 1 <dbl [82]> <chr [6]> <chr [6]> #> 8 QB 8 1 <dbl [78]> <chr [6]> <chr [6]> #> 9 QB 9 1 <dbl [83]> <chr [6]> <chr [6]> #> 10 QB 10 1 <dbl [83]> <chr [6]> <chr [6]> #> # … with 634 more rows
# }