3  WR Rankings

3.1 Packages Needed

library(tidyverse)
library(cfbfastR)
library(DT)

3.2 Load Play-by-Play Data

pbp_2025 <- load_cfb_pbp(seasons = 2025) # mean epa/target

3.3 Load WR Players

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

3.4 Load Necessary CSV Files

receiving <- read.csv("data/receiving_summary.csv") %>% 
  select(player_id, grades_pass_route, yprr, drop_rate, contested_catch_rate) # rec grade, yprr, drop%, contested catch %

3.5 Combine Datasets and Pull Names

wr_values <- wrs %>% 
  left_join(receiving, by = c("id" = "player_id")) %>% 
  drop_na()
wr_values <- wr_values %>% 
  rename(rec_grade = grades_pass_route, cc_rate = contested_catch_rate)
wr_names <- wr_values %>% pull(name)

3.6 Calculate Mean EPA and Combine

receiver_epa <- pbp_2025 %>%
  filter(pass == 1) %>%
  group_by(receiver_player_name) %>%
  summarize(mean_epa = round(mean(EPA, na.rm = TRUE), 3)) %>%
  filter(!is.na(receiver_player_name), receiver_player_name %in% wr_names) %>%
  rename(name = receiver_player_name) %>%
  arrange(-mean_epa)

wr_values <- left_join(wr_values, receiver_epa, by = "name") %>% select(-id)

3.7 Get Mean Values (for testing)

mean(wr_values$rec_grade)

[1] 73.51746

mean(wr_values$yprr)

[1] 2.052857

mean(wr_values$drop_rate)

[1] 6.566667

mean(wr_values$cc_rate)

[1] 48.31905

mean(wr_values$mean_epa)

[1] 0.5302698

3.8 Create Rating Function

get_wr_ratings <- function(input_df) {
  df_wr_copy <- input_df %>% mutate(
    rec_grade = round(pmax(pmin((rec_grade-60) / 3, 10), 0), 2), # 60-90, mean 75
    yprr = round(pmax(pmin((yprr-1.5) * 6.67, 10), 0), 2), # 1.5-3, mean 2.25
    drop_rate = round(pmax(pmin(((100-drop_rate)-88), 10), 0), 2), # 12-2, mean 7
    cc_rate = round(pmax(pmin((cc_rate-35) / 3, 10), 0), 2), # 35-65, mean 50
    mean_epa = round(pmax(pmin((mean_epa) * 10, 10), 0), 2), # 0-1, mean .5
  )
  
  return(df_wr_copy)
}

3.9 Create Final Dataset

wr_ratings <- get_wr_ratings(wr_values) %>% 
  mutate(total = rowSums(select(.,-name, -position, -team, -rank))) %>% 
  arrange(-total) #%>%
  #mutate(pos_rank_aft = row_number())

3.10 Display Ratings

datatable(wr_ratings)