Adding initial plots and code to repo.

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

penalties.R

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+#load necessary packages
+library(cli)
+library(tidyverse)
+library(ggrepel)
+library(ggimage)
+library(ggalt)
+library(nflfastR)
+library(dplyr)
+library(nflreadr)
+library(rstudioapi)
+options(scipen = 9999)
+
+setwd(dirname(getActiveDocumentContext()$path))  
+
+#get pbp and ref data
+data <- nflfastR::load_pbp(2011:2022)
+
+#update team names
+data <- data %>%
+  mutate(
+    penalty_team = case_when(
+      penalty_team == 'LV' ~ 'OAK',
+      penalty_team == 'SD' ~ 'LAC',
+      penalty_team == 'STL' ~ 'LA',
+      TRUE ~ penalty_team
+    ),
+    team_szn = paste0(penalty_team, season)
+  )
+
+#get postseason data by team and game
+post <- data %>%
+  filter(season_type != "REG", penalty == 1) %>%
+  group_by(penalty_team, season, week) %>%
+  summarize(penalty_yards = sum(penalty_yards),
+            penalties = n()) %>%
+  ungroup()
+
+#get regular season data by team and season
+reg <- data %>%
+  filter(season_type == "REG", penalty == 1) %>%
+  group_by(penalty_team, season) %>%
+  summarize(penalty_yards = sum(penalty_yards),
+            penalties = n(),
+            weeks = n_distinct(week)) %>%
+  ungroup()
+
+#get regular season total averages
+reg <- reg %>%
+  mutate(penalty_yards = round((penalty_yards / weeks), 2),
+         penalties = round((penalties / weeks), 2))
+
+#join regular and postseason data
+penalty_stitch <- post %>% left_join(reg, by = c("penalty_team" = "penalty_team", "season" = "season"))
+penalty_stitch <- penalty_stitch %>%
+  select(-c(weeks)) %>%
+  rename(team = penalty_team, penalty_yards = penalty_yards.x,
+         penalties = penalties.x, penalty_yards_reg_avg = penalty_yards.y,
+         penalties_reg_avg = penalties.y)
+#create differences values
+penalty_stitch <- within(penalty_stitch, {yards_diff <- penalty_yards - penalty_yards_reg_avg;
+  penalty_diff <- penalties - penalties_reg_avg})
+
+#get averages for data grouped by season
+season_avgs <- penalty_stitch %>%
+  group_by(season) %>%
+  summarize(penalty_yards = mean(penalty_yards),
+            penalties = mean(penalties),
+            penalty_yards_reg_avg = mean(penalty_yards_reg_avg),
+            penalties_reg_avg = mean(penalties_reg_avg),
+            penalty_diff = mean(penalty_diff),
+            yards_diff = mean(yards_diff)
+            )
+season_avgs$season <- as.factor(season_avgs$season)
+
+#So the column and lines can have different colors
+season_avgs <- within(season_avgs, {penalty_colour <- ifelse(penalty_diff > 0, "darkorange", "turquoise4");
+yards_colour <-ifelse(yards_diff > 0, "darkorange", "turquoise4") })
+
+#####make the plot for # of penalties
+season_avgs %>%
+  ggplot() +
+  #get the lines for seasons
+  geom_segment(data=season_avgs, aes(y = season, yend = season, x=4, xend=7), color="gray85", size=0.15) +
+  #make the dumbbell plot
+  ggalt::geom_dumbbell(aes(y = season, x = penalties, xend = penalties_reg_avg), size = 2,
+                size_x = 5, size_xend = 5, color = season_avgs$penalty_colour, colour_x = "darkorange", colour_xend = "turquoise4") +
+  #add header to top data points
+  geom_text(data=filter(season_avgs, season==2022),
+            aes(x=penalties, y=season, label="Post"),
+            color="darkorange2", size=3.5, vjust=-1.5, fontface="bold") +
+  geom_text(data=filter(season_avgs, season==2022),
+            aes(x=penalties_reg_avg, y=season, label="Regular"),
+            color="turquoise4", size=3.5, vjust=-1.5, fontface="bold") +
+  #add values to data points
+  geom_text(data = season_avgs, aes(x = penalties, y = season, label = sprintf("%0.2f", round(penalties, digits = 2))),
+            color = "darkorange2", size=3.5, vjust=2) +
+  geom_text(data = season_avgs, color = "turquoise4", size=3.5, vjust=2,
+            aes(x = penalties_reg_avg, y = season, label = sprintf("%0.2f", round(penalties_reg_avg, digits = 2)))) +
+  #create Differences section of viz
+  geom_rect(data = season_avgs, aes(xmin = 7, xmax = 7.5, ymin = -Inf, ymax = Inf), fill="grey") +
+  geom_text(data = season_avgs, aes(label=sprintf("%0.2f", abs(round(penalty_diff, digits = 2))), y = season, x=7.25), fontface="bold", size=3.6,
+            color = season_avgs$penalty_colour) +
+  geom_text(data=filter(season_avgs, season==2022), 
+            aes(x = 7.25, y = season, label = "Difference"),
+            color="black", size=4, vjust=-1.5, fontface="bold") +
+  #add labels
+  labs(x = 'Penalties',
+       y = 'Seasons',
+       title = 'Penalties Called in Regular Season VS Postseason',
+       subtitle = 'Differences measured by subtracting postseason penalties called by the team\'s regular season average.',
+       caption = "Data: @nflfastR"
+  ) +
+  #themes and scale
+  theme_bw() +
+  theme(
+    aspect.ratio = 9 / 16,
+    plot.title = element_text(size = 16, hjust = .5, face = 'bold'),
+    plot.subtitle = element_text(size = 12, hjust = .5),
+    axis.text.x = element_blank(),
+    axis.ticks = element_blank(),
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank(),
+    panel.border = element_blank(),
+    plot.caption = element_text(size = 10, vjust = 7, hjust = 0.95),
+    axis.title.y = element_text(size = 12, vjust = 10),
+    axis.title.x = element_text(size = 12, vjust = 2)
+  ) +
+  scale_x_continuous()
+ggsave(path = "plots", filename = "num_penalties.png")
+
+#####make the plot for penalty yards
+season_avgs %>%
+  ggplot() +
+  #get lines for seasons
+  geom_segment(data=season_avgs, aes(y = season, yend = season, x=33, xend=62), color="gray85", size=0.15) +
+  #make the dumbbell plots
+  ggalt::geom_dumbbell(aes(y = season, x = penalty_yards, xend = penalty_yards_reg_avg), size = 2,
+                       size_x = 5, size_xend = 5, color = season_avgs$yards_colour, colour_x = "darkorange", colour_xend = "turquoise4") +
+  #add header to top data points
+  geom_text(data=filter(season_avgs, season==2022),
+            aes(x=penalty_yards, y=season, label="Post"),
+            color="darkorange2", size=3.5, vjust=-1.5, fontface="bold") +
+  geom_text(data=filter(season_avgs, season==2022),
+            aes(x=penalty_yards_reg_avg, y=season, label="Regular"),
+            color="turquoise4", size=3.5, vjust=-1.5, fontface="bold") +
+  #add values to data points
+  geom_text(data = season_avgs, aes(x = penalty_yards, y = season, label = sprintf("%0.2f", round(penalty_yards, digits = 2))),
+            color = "darkorange2", size=3.5, vjust=2) +
+  geom_text(data = season_avgs, color = "turquoise4", size=3.5, vjust=2,
+            aes(x = penalty_yards_reg_avg, y = season, label = sprintf("%0.2f", round(penalty_yards_reg_avg, digits = 2)))) +
+  #create Differences section of viz
+  geom_rect(data = season_avgs, aes(xmin = 60, xmax = 64, ymin = -Inf, ymax = Inf), fill="grey") +
+  geom_text(data = season_avgs, aes(label=sprintf("%0.2f", abs(round(yards_diff, digits = 2))), y = season, x=62), fontface="bold", size=3.6,
+            color = season_avgs$yards_colour) +
+  geom_text(data=filter(season_avgs, season==2022), 
+            aes(x = 62, y = season, label = "Difference"),
+            color="black", size=4, vjust=-2, fontface="bold") +
+  #add labels
+  labs(x = 'Penalty Yards',
+       y = 'Seasons',
+       title = 'Penalty Yards in Regular Season VS Postseason',
+       subtitle = 'Differences measured by subtracting postseason penalties yards by the team\'s regular season average.',
+       caption = "Data: @nflfastR"
+  ) +
+  #themes and scale
+  theme_bw() +
+  theme(
+    aspect.ratio = 9 / 16,
+    plot.title = element_text(size = 16, hjust = .5, face = 'bold'),
+    plot.subtitle = element_text(size = 12, hjust = .5),
+    axis.text.x = element_blank(),
+    axis.ticks = element_blank(),
+    panel.grid.major = element_blank(),
+    panel.grid.minor = element_blank(),
+    panel.border = element_blank(),
+    plot.caption = element_text(size = 10, vjust = 7, hjust = 0.95),
+    axis.title.y = element_text(size = 12, vjust = 10),
+    axis.title.x = element_text(size = 12, vjust = 2)
+  ) +
+  scale_x_continuous()
+ggsave(path = "plots", filename = "penalty_yds.png")
+
+#postseason teams
+team_seasons <- post %>% left_join(reg, by = c("penalty_team" = "penalty_team", "season" = "season"))
+team_seasons <- unique(team_seasons[c("penalty_team", "season")])
+team_seasons <- paste0(team_seasons$penalty_team, team_seasons$season)
+select_data <- data %>% filter(team_szn %in% team_seasons)
+#fix 2021 bonus week
+#do we want this?
+time_series_data <- select_data %>%
+  mutate(
+    week = case_when(
+    season == 2021 & week > 17 ~ as.integer(week - 1),
+    TRUE ~ week
+    )
+  )
+#group the data
+time_series_data <- select_data %>%
+  group_by(penalty_team, season, week, season_type) %>%
+  summarize(pen_yards = sum(penalty_yards),
+            penalties = n()) %>%
+  ungroup()
+
+ts_week_mean <- time_series_data %>%
+  group_by(week, season_type) %>%
+  summarise(pen_yards = mean(pen_yards),
+            penalties = mean(penalties),
+            sample_size = n())
+
+#linear model on non-agg df
+lm.pen.yds <- lm(formula = pen_yards ~ week + season_type, data = time_series_data)
+summary(lm.pen.yds)
+
+#lm.pen.yds <- lm(formula = pen_yards ~ week, data = time_series_data)
+#summary(lm_pen_yds)
+
+pen_yds_predict <- cbind(ts_week_mean, predict(lm.pen.yds, interval = 'confidence',
+                                               newdata = ts_week_mean))
+
+#####penalty yards time series plot
+ggplot(pen_yds_predict, aes(x=week, y=pen_yards, color = season_type)) +
+  geom_point(aes(size = sample_size)) +
+  geom_line() +
+  scale_color_manual(values = c("REG" = "turquoise4", "POST" = "darkorange2")) +
+  geom_line(aes(week, fit, color = "black")) +
+  geom_ribbon(aes(ymin = lwr, ymax = upr), alpha = 0.3) +
+  theme_bw() +
+  theme(
+    aspect.ratio = 9 / 16,
+    plot.title = element_text(size = 30, hjust = .5, face = 'bold'),
+    plot.subtitle = element_text(size = 24, hjust = .5),
+    axis.title.y = element_text(size = 24),
+    axis.title.x = element_text(size = 24),
+    axis.text.y = element_text(size = 16),
+    axis.text.x = element_text(size = 16),
+  ) +
+  labs(x = 'Week',
+       y = 'Penalty Yards',
+       title = 'Average Penalty Yards of Playoff Teams By Week',
+       subtitle = 'Only playoff teams included. Data separated by regular season and postseason.',
+       caption = "Data: @nflfastR")
+
+#####count Penalties time series plot
+ts_week_mean %>%
+  ggplot(aes(x=week, y=penalties, color = season_type)) +
+  geom_point(aes(size = sample_size)) +
+  geom_line() +
+  scale_color_manual(values = c("REG" = "turquoise4", "POST" = "darkorange2")) +
+  theme_bw() +
+  theme(
+    aspect.ratio = 9 / 16,
+    plot.title = element_text(size = 16, hjust = .5, face = 'bold'),
+    plot.subtitle = element_text(size = 12, hjust = .5),
+    axis.title.y = element_text(size = 12),
+    axis.title.x = element_text(size = 12)
+  ) +
+  labs(x = 'Week',
+       y = 'Penalties',
+       title = 'Average Number of Penalties of Playoff Teams By Week',
+       subtitle = 'Only playoff teams included. Data separated by regular season and postseason.',
+       caption = "Data: @nflfastR")

penalties.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX