Packages Needed

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(cfbfastR)
library(DT)
## Warning: package 'DT' was built under R version 4.4.3

Read CSV File

WR_Stats <- read.csv("WR_Rankings.csv") %>%
  arrange(rank) %>%
  mutate(pos_rank_bef = row_number())
datatable(WR_Stats)

Load Play-By-Play Data

pbp_2024 <- load_cfb_pbp(seasons = 2024)

Get Player Names

wr_players <- WR_Stats$player
wr_players
##  [1] "Travis Hunter"         "Tetairoa McMillan"     "Luther Burden III"    
##  [4] "Emeka Egbuka"          "Matthew Golden"        "Elic Ayomanor"        
##  [7] "Jack Bech"             "Jayden Higgins"        "Xavier Restrepo"      
## [10] "Tre Harris"            "Jaylin Noel"           "Jalen Royals"         
## [13] "Savion Williams"       "Tez Johnson"           "Isaiah Bond"          
## [16] "Tory Horton"           "Pat Bryant"            "Kobe Hudson"          
## [19] "Kyle Williams"         "Isaac TeSlaa"          "Nick Nash"            
## [22] "Jaylin Lane"           "Tai Felton"            "Antwane Wells Jr."    
## [25] "Dont'e Thornton Jr."   "KeAndre Lambert-Smith" "Kaden Prather"        
## [28] "Chimere Dike"          "Ricky White III"       "Efton Chism III"      
## [31] "Jimmy Horn Jr."        "Samuel Brown Jr."      "Will Sheppard"        
## [34] "LaJohntay Wester"      "Theo Wease Jr."        "Kyren Lacy"           
## [37] "Zakhari Franklin"      "Roc Taylor"            "Jackson Meeks"        
## [40] "Bru McCoy"             "Elijhah Badger"        "Da'Quan Felton"       
## [43] "Joey Hobert"           "Julian Fleming"        "Beaux Collins"        
## [46] "Ja'Corey Brooks"       "Moose Muhammad III"    "Konata Mumpfield"     
## [49] "Arian Smith"

Calculate Total EPA

receiver_summary <- pbp_2024 %>%
  filter(completion == 1) %>%
  group_by(receiver_player_name) %>%
  summarize(total_plays = n(), total_epa = sum(EPA, na.rm = TRUE)) %>%
  filter(!is.na(receiver_player_name), receiver_player_name %in% wr_players) %>%
  rename(player = receiver_player_name)

datatable(receiver_summary)

Combine Datasets

combined_wr <- WR_Stats %>%
  left_join(receiver_summary, by = "player")
datatable(combined_wr)

Get Mean Values

mean(combined_wr$rec_grade)
## [1] 75.25102
mean(combined_wr$yprr)
## [1] 2.281837
mean(combined_wr$drop)
## [1] 6.791837
mean(combined_wr$ctc)
## [1] 53.06327
mean(combined_wr$total_epa)
## [1] 65.21414
summary(combined_wr$total_epa)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.135  39.860  68.651  65.214  86.317 128.405

Create Values Function

get_wr_values <- 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 = round(pmax(pmin(((100-drop)-90) * 1.67, 10), 0), 2), # 10-4, mean 7
    ctc = round(pmax(pmin((ctc-35) / 3, 10), 0), 2), # 35-65, mean 50
    total_epa = round(pmax(pmin((total_epa-30) / 7, 10), 0), 2), # 30-100, mean 65
  )
  return(df_wr_copy)
}

Create Final Dataset

new_stats_wr <- get_wr_values(combined_wr) %>% 
  mutate(total = rowSums(select(., -player, -adp, -total_plays, -rank, -pos_rank_bef, -team))) %>% 
  arrange(-total) %>% 
  mutate(pos = "WR", pos_rank_aft = row_number(), pos_rank_diff = pos_rank_bef-pos_rank_aft) %>%
  select(player, rec_grade, yprr, drop, ctc, total_epa, total, rank, pos, team, pos_rank_bef, pos_rank_aft, pos_rank_diff)
datatable(new_stats_wr)

Get Total Value and Rank

get the dataset that only contains the total and the ranks

wr_stats_total <- new_stats_wr %>%
  select(player, total, rank, pos, team, pos_rank_bef, pos_rank_aft, pos_rank_diff)
datatable(wr_stats_total)

Download Final Rankings

write.csv(wr_stats_total, "wr_stats_total.csv", row.names = FALSE)