10  ED Rankings

10.1 Packages Needed

library(tidyverse)
library(DT)

10.2 Load ED Players

eds <- read.csv("data/players.csv") %>% filter(position == "ED")

10.3 Load Necessary CSV Files

defense <- read.csv("data/defense_summary.csv") %>% 
  select(player_id, missed_tackle_rate, grades_pass_rush_defense, grades_run_defense) # miss %, prsh_grade, rdef_grade
prsh_defense <- read.csv("data/pass_rush_summary.csv") %>% select(player_id, pass_rush_win_rate, prp) # prsh_win_p, prp
run_defense <- read.csv("data/run_defense_summary.csv") %>% select(player_id, stop_percent) # run_stop_p

10.4 Combine Datasets

ed_values <- eds %>% 
  left_join(defense, by = c("id" = "player_id")) %>% 
  drop_na()
ed_values <- ed_values %>% 
  left_join(prsh_defense, by = c("id" = "player_id")) %>% 
  drop_na()
ed_values <- ed_values %>% left_join(run_defense, by = c("id" = "player_id")) %>% drop_na()
ed_values <- ed_values %>% 
  rename(miss_p = missed_tackle_rate, rdef_grade = grades_run_defense, prsh_grade = grades_pass_rush_defense, prsh_win_p = pass_rush_win_rate, run_stop_p = stop_percent) %>%
  select(-id)

10.5 Get Mean Values (for testing)

mean(ed_values$miss_p)

[1] 17.51064

mean(ed_values$rdef_grade)

[1] 73.05532

mean(ed_values$prsh_grade)

[1] 77.98723

mean(ed_values$prsh_win_p)

[1] 15.51915

mean(ed_values$prp)

[1] 8.408511

mean(ed_values$run_stop_p)

[1] 6.940426

10.6 Create Rating Function

get_ed_ratings <- function(input_df) {
  df_ed_copy <- input_df %>% mutate(
    prsh_grade = round(pmax(pmin((prsh_grade-70) / 2, 10), 0), 2),  # 70-90, mean 80
    rdef_grade = round(pmax(pmin((rdef_grade-65) / 2, 10), 0), 2), # 65-85, mean 75
    prsh_win_p = round(pmax(pmin((prsh_win_p-10), 10), 0), 2), # 10-20, mean 15
    run_stop_p = round(pmax(pmin((run_stop_p-4)*2, 10), 0), 2), # 4-9, mean 6.5
    prp = round(pmax(pmin((prp-6)/1.2, 5), 0), 2), # 6-12, mean 9, worth 5
    miss_p = round(pmax(pmin(((100-miss_p)-75) / 3, 5), 0), 2), # 25-10, mean 17.5, worth 5
  )
  
  return(df_ed_copy)
}

10.7 Create Final Dataset

ed_ratings <- get_ed_ratings(ed_values) %>% 
  mutate(total = rowSums(select(.,-name, -position, -team, -rank))) %>% 
  arrange(-total) #%>%
  #mutate(pos_rank_aft = row_number())

10.8 Display Ratings

datatable(ed_ratings)