library(tidyverse)

library(nflverse)

### QUESTION #1

pbp <- nflreadr::load_pbp(2022) %>%

filter(season_type == "REG")

rb_third_down <- pbp %>%

filter(play_type == "run" & !is.na(rusher)) %>%

filter(down == 3 & ydstogo <= 10) %>%

group_by(rusher, rusher_player_id) %>%

summarize(

total = n(),

total_first = sum(yards_gained >= ydstogo, na.rm = TRUE),

total_pct = total_first / total,

team = last(posteam)) %>%

filter(total >= 20) %>%

arrange(-total_pct)

ggplot(rb_third_down, aes(x = reorder(rusher_player_id, -total_pct), y = total_pct)) +

geom_col(aes(color = team, fill = team), width = 0.5) +

nflplotR::scale_color_nfl(type = "secondary") +

nflplotR::scale_fill_nfl(type = "primary") +

scale_y_continuous(breaks = scales::pretty_breaks(),

labels = scales::percent_format(),

expand = c(0,0)) +

xlab("") +

ylab("1st Down Percentage on 3rd-Down Rushing Attempts") +

theme_minimal() +

theme(axis.text.x = nflplotR::element_nfl_headshot()) +

labs(title = "Which RBs Converted Most 3rd Down Attempts?",

subtitle = "2022 Regular Season")

### QUESTION #2

pbp <- nflreadr::load_pbp(2022) %>%

filter(season_type == "REG")

offensive_epa <- pbp %>%

filter(!is.na(posteam) & !is.na(down)) %>%

group_by(posteam) %>%

summarize(mean_epa = mean(epa, na.rm = TRUE))

ggplot(offensive_epa, aes(x = mean_epa, y = reorder(posteam, mean_epa))) +

geom_col(aes(color = posteam, fill = posteam), width = 0.75) +

nflplotR::scale_color_nfl(type = "secondary") +

nflplotR::scale_fill_nfl(type = "primary") +

geom_vline(xintercept = 0, color = "black", linewidth = 1) +

nflplotR::geom_nfl_logos(aes(team_abbr = posteam), width = 0.055) +

theme_minimal() +

theme(axis.text.y = element_blank()) +

xlab("Offensive Mean EPA") +

ylab("") +

labs(title = "Avgerage EPA Per Play",

subtitle = "2022 Regular Season")