Runs the bootstrapped resampling of player week outcomes on the latest rankings and rosters for a given number of seasons and weeks per season.
Usage
ffs_generate_projections(
adp_outcomes,
latest_rankings,
n_seasons = 100,
weeks = 1:14,
rosters = NULL
)Arguments
- adp_outcomes
a dataframe of adp-based weekly outcomes, as created by
ffs_adp_outcomes()- latest_rankings
a dataframe of rankings, as created by
ffs_latest_rankings()- n_seasons
number of seasons, default is 100
- weeks
a numeric vector of weeks to simulate, defaults to 1:14
- rosters
a dataframe of rosters, as created by
ffs_rosters()- optional, reduces computation to just rostered players
Value
a dataframe of weekly scores for each player in the simulation, approximately of length n_seasons x n_weeks x latest_rankings
Examples
# \donttest{
# cached examples
adp_outcomes <- .ffs_cache("adp_outcomes.rds")
latest_rankings <- .ffs_cache("latest_rankings.rds")
ffs_generate_projections(adp_outcomes, latest_rankings)
#> season fantasypros_id player pos team bye ecr sd rank
#> 1: 1 16413 Patrick Mahomes II QB KCC 12 1.32 0.69 1
#> 2: 1 16413 Patrick Mahomes II QB KCC 12 1.32 0.69 1
#> 3: 1 16413 Patrick Mahomes II QB KCC 12 1.32 0.69 1
#> 4: 1 16413 Patrick Mahomes II QB KCC 12 1.32 0.69 1
#> 5: 1 16413 Patrick Mahomes II QB KCC 12 1.32 0.69 1
#> ---
#> 993436: 96 19534 Tarik Black WR IND 14 239.50 20.50 243
#> 993437: 96 19534 Tarik Black WR IND 14 239.50 20.50 243
#> 993438: 96 19534 Tarik Black WR IND 14 239.50 20.50 243
#> 993439: 96 19534 Tarik Black WR IND 14 239.50 20.50 243
#> 993440: 96 19534 Tarik Black WR IND 14 239.50 20.50 243
#> scrape_date week projection gp_model projected_score
#> 1: 2021-09-03 1 7.24 1 7.24
#> 2: 2021-09-03 2 16.92 1 16.92
#> 3: 2021-09-03 3 27.76 1 27.76
#> 4: 2021-09-03 4 19.22 1 19.22
#> 5: 2021-09-03 5 13.50 1 13.50
#> ---
#> 993436: 2021-09-03 10 0.00 0 0.00
#> 993437: 2021-09-03 11 4.40 0 0.00
#> 993438: 2021-09-03 12 2.10 0 0.00
#> 993439: 2021-09-03 13 0.00 0 0.00
#> 993440: 2021-09-03 14 0.00 0 0.00
# }