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benfb/pitcher_by_inning_2016.r

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pitcher_by_inning_2016.r
library(baseballr)
library(Lahman)
library(dplyr)
library(ggplot2)
library(reshape2)
library(stringr)
library(tidyr)
library(ggthemes)
library(grid)
library(gridExtra)
hendricks <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 543294)
hendricks_by_inning <- hendricks %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
hendricks_by_inning_long <- melt(hendricks_by_inning, id = c("inning", "pitch_type"))
p1 <- ggplot(hendricks_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Kyle Hendricks",
colour = "Pitch",
x = "Inning") +
theme_fivethirtyeight()
scherzer <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 453286)
scherzer_by_inning <- scherzer %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
scherzer_by_inning_long <- melt(scherzer_by_inning, id = c("inning", "pitch_type"))
p2 <- ggplot(scherzer_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Max Scherzer",
colour = "Pitch") +
theme_fivethirtyeight()
kluber_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 446372) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p3 <- ggplot(kluber_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Corey Kluber",
colour = "Pitch") +
theme_fivethirtyeight()
porcello_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 519144) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p4 <- ggplot(porcello_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Rick Porcello",
colour = "Pitch") +
theme_fivethirtyeight()
lester_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 452657) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p5 <- ggplot(lester_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Jon Lester",
colour = "Pitch") +
theme_fivethirtyeight()
verlander_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 434378) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p6 <- ggplot(verlander_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Justin Verlander",
colour = "Pitch") +
theme_fivethirtyeight()
price_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456034) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p7 <- ggplot(price_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "David Price",
colour = "Pitch") +
theme_fivethirtyeight()
cueto_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456501) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p8 <- ggplot(cueto_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Johnny Cueto",
colour = "Pitch") +
theme_fivethirtyeight()
bumgarner_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 518516) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(start_speed)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p9 <- ggplot(bumgarner_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Madison Bumgarner",
colour = "Pitch") +
theme_fivethirtyeight()
multi <- grid.arrange(p1, p2, p3, p4, p5, p6, p8, p7, p9, ncol = 3)
ggsave("velo.png", multi, width = 30, height = 20, units = "cm")
### SPIN
hendricks <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 543294)
hendricks_by_inning <- hendricks %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
hendricks_by_inning_long <- melt(hendricks_by_inning, id = c("inning", "pitch_type"))
p1 <- ggplot(hendricks_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Kyle Hendricks",
colour = "Pitch",
x = "Inning") +
theme_fivethirtyeight()
scherzer <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 453286)
scherzer_by_inning <- scherzer %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
scherzer_by_inning_long <- melt(scherzer_by_inning, id = c("inning", "pitch_type"))
p2 <- ggplot(scherzer_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Max Scherzer",
colour = "Pitch") +
theme_fivethirtyeight()
kluber_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 446372) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p3 <- ggplot(kluber_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Corey Kluber",
colour = "Pitch") +
theme_fivethirtyeight()
porcello_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 519144) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p4 <- ggplot(porcello_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Rick Porcello",
colour = "Pitch") +
theme_fivethirtyeight()
lester_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 452657) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p5 <- ggplot(lester_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Jon Lester",
colour = "Pitch") +
theme_fivethirtyeight()
verlander_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 434378) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p6 <- ggplot(verlander_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Justin Verlander",
colour = "Pitch") +
theme_fivethirtyeight()
price_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456034) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p7 <- ggplot(price_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "David Price",
colour = "Pitch") +
theme_fivethirtyeight()
cueto_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456501) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p8 <- ggplot(cueto_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Johnny Cueto",
colour = "Pitch") +
theme_fivethirtyeight()
bumgarner_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 518516) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(spin_rate)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p9 <- ggplot(bumgarner_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Madison Bumgarner",
colour = "Pitch") +
theme_fivethirtyeight()
multi <- grid.arrange(p1, p2, p3, p4, p5, p6, p8, p7, p9, ncol = 3)
ggsave("spin.png", multi, width = 30, height = 20, units = "cm")
### BREAK
hendricks <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 543294)
hendricks_by_inning <- hendricks %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
hendricks_by_inning_long <- melt(hendricks_by_inning, id = c("inning", "pitch_type"))
p1 <- ggplot(hendricks_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Kyle Hendricks",
colour = "Pitch",
x = "Inning") +
theme_fivethirtyeight()
scherzer <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 453286)
scherzer_by_inning <- scherzer %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN")
scherzer_by_inning_long <- melt(scherzer_by_inning, id = c("inning", "pitch_type"))
p2 <- ggplot(scherzer_by_inning_long, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Max Scherzer",
colour = "Pitch") +
theme_fivethirtyeight()
kluber_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 446372) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p3 <- ggplot(kluber_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Corey Kluber",
colour = "Pitch") +
theme_fivethirtyeight()
porcello_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 519144) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p4 <- ggplot(porcello_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Rick Porcello",
colour = "Pitch") +
theme_fivethirtyeight()
lester_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 452657) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p5 <- ggplot(lester_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Jon Lester",
colour = "Pitch") +
theme_fivethirtyeight()
verlander_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 434378) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p6 <- ggplot(verlander_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Justin Verlander",
colour = "Pitch") +
theme_fivethirtyeight()
price_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456034) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p7 <- ggplot(price_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "David Price",
colour = "Pitch") +
theme_fivethirtyeight()
cueto_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456501) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p8 <- ggplot(cueto_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Johnny Cueto",
colour = "Pitch") +
theme_fivethirtyeight()
bumgarner_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 518516) %>%
group_by(pitch_type, inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(break_length)), na.rm = TRUE)
) %>%
filter(pitch_type != "NA", pitch_type != "IN", pitch_type != "PO") %>%
melt(id = c("inning", "pitch_type"))
p9 <- ggplot(bumgarner_by_inning, aes(x=as.factor(inning), y=value, group=pitch_type, colour=pitch_type)) +
geom_line() +
geom_point() +
labs(title = "Madison Bumgarner",
colour = "Pitch") +
theme_fivethirtyeight()
multi <- grid.arrange(p1, p2, p3, p4, p5, p6, p8, p7, p9, ncol = 3)
ggsave("break.png", multi, width = 30, height = 20, units = "cm")
### EXIT VELOCITY
hendricks_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 543294) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p1 <- ggplot(hendricks_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Kyle Hendricks") +
theme_fivethirtyeight()
scherzer_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 453286) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p2 <- ggplot(scherzer_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Max Scherzer") +
theme_fivethirtyeight()
kluber_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 446372) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p3 <- ggplot(kluber_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Corey Kluber") +
theme_fivethirtyeight()
porcello_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 519144) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p4 <- ggplot(porcello_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Rick Porcello") +
theme_fivethirtyeight()
lester_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 452657) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p5 <- ggplot(lester_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Jon Lester") +
theme_fivethirtyeight()
verlander_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 434378) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p6 <- ggplot(verlander_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Justin Verlander") +
theme_fivethirtyeight()
price_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456034) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p7 <- ggplot(price_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "David Price") +
theme_fivethirtyeight()
cueto_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456501) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p8 <- ggplot(cueto_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Johnny Cueto") +
theme_fivethirtyeight()
bumgarner_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 518516) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_speed)), na.rm = TRUE)
)
p9 <- ggplot(bumgarner_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Madison Bumgarner") +
theme_fivethirtyeight()
multi <- grid.arrange(p1, p2, p3, p4, p5, p6, p8, p7, p9, ncol = 3)
ggsave("hitspeed.png", multi, width = 30, height = 20, units = "cm")
### HIT DISTANCE
hendricks_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 543294) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p1 <- ggplot(hendricks_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Kyle Hendricks") +
theme_fivethirtyeight()
scherzer_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 453286) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p2 <- ggplot(scherzer_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Max Scherzer") +
theme_fivethirtyeight()
kluber_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 446372) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p3 <- ggplot(kluber_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Corey Kluber") +
theme_fivethirtyeight()
porcello_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 519144) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p4 <- ggplot(porcello_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Rick Porcello") +
theme_fivethirtyeight()
lester_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 452657) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p5 <- ggplot(lester_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Jon Lester") +
theme_fivethirtyeight()
verlander_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 434378) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p6 <- ggplot(verlander_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Justin Verlander") +
theme_fivethirtyeight()
price_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456034) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p7 <- ggplot(price_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "David Price") +
theme_fivethirtyeight()
cueto_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 456501) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p8 <- ggplot(cueto_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Johnny Cueto") +
theme_fivethirtyeight()
bumgarner_by_inning <- scrape_statcast_savant_pitcher(start_date = "2016-04-05", end_date = "2016-10-15", pitcherid = 518516) %>%
group_by(inning) %>%
summarize(
avg_mph = mean(as.numeric(as.character(hit_distance_sc)), na.rm = TRUE)
)
p9 <- ggplot(bumgarner_by_inning, aes(x=as.factor(inning), y=avg_mph, group=1)) +
geom_line() +
geom_point() +
labs(title = "Madison Bumgarner") +
theme_fivethirtyeight()
multi <- grid.arrange(p1, p2, p3, p4, p5, p6, p8, p7, p9, ncol = 3)
ggsave("hitdistance.png", multi, width = 30, height = 20, units = "cm")
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