NFL Team EPA Rankings

Load Packages

library(tidyverse)

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library(nflfastR)

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library(formattable)

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library(circlize)

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## circlize version 0.4.16
## CRAN page: https://cran.r-project.org/package=circlize
## Github page: https://github.com/jokergoo/circlize
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library(DT)

## Warning: package 'DT' was built under R version 4.4.3

Load Play-By-Play

pbp <- load_pbp(2025)

get_team_data <- function(team_input, pbp) {
  # Get offensive rush epa
  off_rush <- pbp %>% 
    filter(posteam == team_input, rush == 1) %>%
    group_by(posteam) %>%
    summarize(o_r_epa = round(mean(epa, na.rm = TRUE), 3)) %>%
    rename(team = posteam)
  
  # Get offensive pass epa
  off_pass <- pbp %>% 
    filter(posteam == team_input, pass == 1) %>%
    group_by(posteam) %>%
    summarize(o_p_epa = round(mean(epa, na.rm = TRUE), 3)) %>%
    select(o_p_epa)
  
  # Get defensive rush epa
  def_rush <- pbp %>% 
    filter(defteam == team_input, rush == 1) %>%
    group_by(defteam) %>%
    summarize(d_r_epa = round(mean(epa, na.rm = TRUE), 3)) %>%
    select(d_r_epa)
  
  # Get defensive pass epa
  def_pass <- pbp %>% 
    filter(defteam == team_input, pass == 1) %>%
    group_by(defteam) %>%
    summarize(d_p_epa = round(mean(epa, na.rm = TRUE), 3)) %>%
    select(d_p_epa)
  
  result <- cbind(off_rush, off_pass, def_rush, def_pass)
  return(result)
}

teams <- unique(na.omit(pbp$posteam))

team_results <- tibble()
for (i in teams) {
  team_results <- bind_rows(team_results, get_team_data(i, pbp))
}

ranks <- team_results %>%
  arrange(-o_r_epa) %>%
  mutate(o_r_rank = row_number()) %>%
  arrange(-o_p_epa) %>%
  mutate(o_p_rank = row_number()) %>%
  arrange(d_r_epa) %>%
  mutate(d_r_rank = row_number()) %>%
  arrange(d_p_epa) %>%
  mutate(d_p_rank = row_number(), 
    avg_rank = round((o_r_rank+o_p_rank+d_r_rank+d_p_rank) / 4, 1)) %>%
  arrange(avg_rank)
  
datatable(ranks)

pbp2024 <- load_pbp(2024)

teams <- unique(na.omit(pbp$posteam))

team_results_2024 <- tibble()
for (i in teams) {
  team_results_2024 <- bind_rows(team_results_2024, get_team_data(i, pbp2024))
}

ranks_2024 <- team_results_2024 %>%
  arrange(-o_r_epa) %>%
  mutate(o_r_rank = row_number()) %>%
  arrange(-o_p_epa) %>%
  mutate(o_p_rank = row_number()) %>%
  arrange(d_r_epa) %>%
  mutate(d_r_rank = row_number()) %>%
  arrange(d_p_epa) %>%
  mutate(d_p_rank = row_number(), 
    avg_rank = round((o_r_rank+o_p_rank+d_r_rank+d_p_rank) / 4, 1)) %>%
  arrange(avg_rank)
  
datatable(ranks_2024)