Calculate predicted points using down and distance — cfbd_metrics_ppa

Calculate predicted points using down and distance

Usage

cfbd_metrics_ppa_predicted(down, distance)

Arguments

down: (Integer required): Down filter
distance: (Integer required): Distance filter

Value

cfbd_metrics_ppa_predicted() - A data frame with 2 variables:

yard_line: integer.: Yards to goal
predicted_points: character.: Predicted points at in that down-distance-yardline scenario

Examples

# \donttest{
  try(cfbd_metrics_ppa_predicted(down = 1, distance = 10))
#> ── PPA data from CollegeFootballData.com ───────────────────── cfbfastR 1.9.5 ──
#> ℹ Data updated: 2024-02-01 16:00:39 UTC
#> # A tibble: 90 × 2
#>    yard_line predicted_points    
#>        <int> <chr>               
#>  1         1 0.008320148130590788
#>  2         2 0.024817699099273227
#>  3         3 0.04248143826009887 
#>  4         4 0.061392920949176144
#>  5         5 0.08163795196519619 
#>  6         6 0.10330653921897337 
#>  7         7 0.1264927880979494  
#>  8         8 0.1512947258089934  
#>  9         9 0.1778140439751219  
#> 10        10 0.20615574686279547 
#> # ℹ 80 more rows

  try(cfbd_metrics_ppa_predicted(down = 3, distance = 10))
#> ── PPA data from CollegeFootballData.com ───────────────────── cfbfastR 1.9.5 ──
#> ℹ Data updated: 2024-02-01 16:00:39 UTC
#> # A tibble: 90 × 2
#>    yard_line predicted_points    
#>        <int> <chr>               
#>  1         1 -0.3352571473205046 
#>  2         2 -0.332057330581474  
#>  3         3 -0.32861257614103323
#>  4         4 -0.32490289156437324
#>  5         5 -0.3209066984336637 
#>  6         6 -0.3166007167339968 
#>  7         7 -0.31195984266280163
#>  8         8 -0.30695701984266943
#>  9         9 -0.3015631040009641 
#> 10        10 -0.29574672128389334
#> # ℹ 80 more rows
# }