knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
library(readxl)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(ggplot2)
library(knitr)
# Load the data
Shore624 <- read_excel("C:/Users/Franco Castagliuolo/OneDrive - Bentley University/Neers 24/Pitchers/Shore 624/Shore 624.xlsx")
# Filter the data for the pitcher Aidan Krupp
Aidan_Krupp_data <- Shore624 %>%
filter(Pitcher == "Krupp, Aidan")
# Create a detailed table for each pitch
detailed_pitch_table <- Aidan_Krupp_data %>%
select(AutoPitchType, RelSpeed, SpinRate, SpinAxis, HorzBreak, InducedVertBreak, PitchCall, RelHeight, RelSide, Extension) %>%
rename(
ReleaseSpeed = RelSpeed,
Tilt = SpinAxis,
HorizontalBreak = HorzBreak,
InducedVerticalBreak = InducedVertBreak,
ReleaseHeight = RelHeight,
ReleaseSide = RelSide
) %>%
mutate(
ReleaseSpeed = round(ReleaseSpeed, 2),
SpinRate = round(SpinRate, 2),
Tilt = round(Tilt, 2),
HorizontalBreak = round(HorizontalBreak, 2),
InducedVerticalBreak = round(InducedVerticalBreak, 2),
ReleaseHeight = round(ReleaseHeight, 2),
ReleaseSide = round(ReleaseSide, 2),
Extension = round(Extension, 2),
ClockTilt = round((Tilt / 30) %% 12, 1) # Interpret Tilt as clock face
)
# Display the detailed table
knitr::kable(detailed_pitch_table, caption = "Detailed Pitch Table for Aidan Krupp")
Detailed Pitch Table for Aidan Krupp
| Changeup |
86.31 |
1984.39 |
269.34 |
21.57 |
1.62 |
FoulBallNotFieldable |
4.29 |
3.19 |
5.35 |
9.0 |
| Changeup |
84.31 |
1859.46 |
269.01 |
21.40 |
1.79 |
InPlay |
4.21 |
3.01 |
5.60 |
9.0 |
| Changeup |
85.14 |
1923.23 |
265.76 |
21.19 |
2.94 |
BallCalled |
4.25 |
2.98 |
5.52 |
8.9 |
| Changeup |
85.42 |
1926.13 |
245.30 |
18.55 |
9.89 |
BallCalled |
4.10 |
2.88 |
5.62 |
8.2 |
| Changeup |
85.96 |
1898.63 |
272.87 |
20.68 |
0.30 |
BallCalled |
4.20 |
2.96 |
5.71 |
9.1 |
| Changeup |
84.03 |
1903.53 |
250.38 |
20.52 |
8.75 |
BallCalled |
4.14 |
2.83 |
5.56 |
8.3 |
| Changeup |
85.72 |
1878.96 |
264.62 |
22.27 |
3.53 |
BallCalled |
4.03 |
2.85 |
5.62 |
8.8 |
| Changeup |
85.43 |
1922.78 |
257.27 |
21.38 |
6.24 |
BallCalled |
4.04 |
2.86 |
5.67 |
8.6 |
| Sinker |
87.42 |
2013.51 |
250.29 |
18.90 |
8.08 |
FoulBallNotFieldable |
4.06 |
2.97 |
5.68 |
8.3 |
| Changeup |
85.93 |
1903.90 |
249.40 |
20.87 |
9.16 |
InPlay |
4.04 |
3.07 |
5.78 |
8.3 |
| Changeup |
84.14 |
1906.69 |
254.45 |
19.46 |
6.79 |
FoulBallNotFieldable |
4.05 |
3.06 |
5.55 |
8.5 |
| Changeup |
85.56 |
1940.94 |
253.60 |
18.69 |
6.83 |
FoulBallNotFieldable |
4.12 |
3.06 |
5.56 |
8.5 |
| Changeup |
86.62 |
1953.22 |
259.59 |
21.00 |
5.22 |
StrikeSwinging |
4.13 |
3.04 |
5.52 |
8.7 |
| Changeup |
84.69 |
1984.95 |
259.33 |
19.78 |
5.08 |
BallCalled |
3.95 |
3.00 |
5.71 |
8.6 |
| Changeup |
85.77 |
1993.15 |
266.26 |
21.89 |
2.82 |
FoulBallNotFieldable |
4.11 |
2.96 |
5.44 |
8.9 |
| Changeup |
85.52 |
1889.63 |
255.94 |
26.48 |
7.84 |
BallCalled |
3.95 |
2.93 |
5.53 |
8.5 |
| Changeup |
84.63 |
1942.22 |
254.18 |
23.00 |
7.77 |
FoulBallNotFieldable |
3.96 |
3.04 |
5.58 |
8.5 |
| Changeup |
85.77 |
1876.73 |
255.03 |
20.30 |
6.77 |
InPlay |
3.95 |
2.86 |
5.47 |
8.5 |
# Calculate the total number of pitches
total_pitches <- nrow(detailed_pitch_table)
# Create a summary table
pitch_summary <- detailed_pitch_table %>%
group_by(AutoPitchType) %>%
summarise(
TotalPitches = n(),
Usage = sprintf("%.2f%%", n() / total_pitches * 100),
Balls = sum(PitchCall == "BallCalled"),
Strikes = sum(PitchCall != "BallCalled"), # Count everything not a ball as a strike
BallPercentage = sprintf('%.2f%%', Balls / TotalPitches * 100),
StrikePercentage = sprintf('%.2f%%', Strikes / TotalPitches * 100),
AvgVelocity = round(mean(ReleaseSpeed, na.rm = TRUE), 2),
AvgSpinRate = round(mean(SpinRate, na.rm = TRUE), 2),
AvgInducedVertBreak = round(mean(InducedVerticalBreak, na.rm = TRUE), 2),
AvgHorzBreak = round(mean(HorizontalBreak, na.rm = TRUE), 2),
AvgTilt = round(mean(Tilt, na.rm = TRUE), 2),
AvgClockTilt = round(mean(ClockTilt, na.rm = TRUE), 1), # Clock face interpretation
AvgReleaseHeight = round(mean(ReleaseHeight, na.rm = TRUE), 2),
AvgReleaseSide = round(mean(ReleaseSide, na.rm = TRUE), 2),
AvgExtension = round(mean(Extension, na.rm = TRUE), 2)
) %>%
select(AutoPitchType, Usage, everything())
# Display the total number of pitches
cat("Total number of pitches thrown: ", total_pitches, "\n")
## Total number of pitches thrown: 18
# Display the summary table
knitr::kable(pitch_summary, caption = "Summary Pitch Table for Aidan Krupp")
Summary Pitch Table for Aidan Krupp
| Changeup |
94.44% |
17 |
8 |
9 |
47.06% |
52.94% |
85.35 |
1922.86 |
5.49 |
21.12 |
258.96 |
8.6 |
4.09 |
2.98 |
5.58 |
| Sinker |
5.56% |
1 |
0 |
1 |
0.00% |
100.00% |
87.42 |
2013.51 |
8.08 |
18.90 |
250.29 |
8.3 |
4.06 |
2.97 |
5.68 |
# Calculate maximum fastball velocity
max_fb_velocity <- detailed_pitch_table %>%
filter(AutoPitchType %in% c("Four-Seam", "Two-Seam", "Sinker", "Cutter")) %>%
summarise(MaxFBVelocity = max(ReleaseSpeed, na.rm = TRUE)) %>%
pull(MaxFBVelocity)
# Display the maximum fastball velocity
cat("Aidan Krupp maximum FB velocity: ", max_fb_velocity, "mph\n")
## Aidan Krupp maximum FB velocity: 87.42 mph
# Prepare data for plotting pitch locations
pitch_location_data <- Aidan_Krupp_data %>%
select(AutoPitchType, PlateLocHeight, PlateLocSide, PitchCall) %>%
rename(
PitchHeight = PlateLocHeight,
PitchSide = PlateLocSide
) %>%
mutate(
SwingTake = ifelse(PitchCall %in% c("StrikeSwinging", "FoulBallNonSwinging", "FoulBallFieldable", "FoulBallNotFieldable", "InPlay"), "Swing", "Take"),
Chase = ifelse(SwingTake == "Swing" & (PitchSide < -0.75 | PitchSide > 0.75 | PitchHeight < 1.5 | PitchHeight > 3.5), "Chase", "Non-Chase")
)
# Create the scatter plot with specified strike zone boxes
ggplot(pitch_location_data, aes(x = PitchSide, y = PitchHeight, color = SwingTake, shape = Chase)) +
geom_point(size = 3) + # Increase point size
geom_rect(aes(xmin = -0.5, xmax = 0.5, ymin = 1.75, ymax = 3.25), fill = NA, color = "red", linetype = "solid", size = 1) + # Red box
geom_rect(aes(xmin = -0.75, xmax = 0.75, ymin = 1.5, ymax = 3.5), fill = NA, color = "black", linetype = "solid", size = 1) + # Black box
geom_rect(aes(xmin = -1.25, xmax = 1.25, ymin = 1.25, ymax = 3.75), fill = NA, color = "gray", linetype = "solid", size = 1) + # Gray box
scale_x_continuous(limits = c(-2, 2)) +
scale_y_continuous(limits = c(0, 5)) +
coord_fixed(ratio = 1) + # Adjust ratio to shrink vertical distance
labs(title = "Pitch Locations for Aidan Krupp",
x = "Horizontal Location (feet)",
y = "Vertical Location (feet)",
color = "Swing/Take",
shape = "Chase") +
facet_wrap(~ AutoPitchType) + # Create individual graphs for each pitch type
theme_minimal() +
theme(
legend.position = "right",
panel.grid.major = element_line(color = "grey80"),
panel.grid.minor = element_line(color = "grey90"),
axis.text = element_text(color = "black"),
axis.title = element_text(color = "black"),
plot.title = element_text(color = "black"),
legend.background = element_rect(fill = "white", color = NA),
legend.key = element_rect(fill = "white", color = NA),
legend.text = element_text(color = "black"),
legend.title = element_text(color = "black")
)
# Create the scatter plot for horizontal and vertical breaks
ggplot(detailed_pitch_table, aes(x = HorizontalBreak, y = InducedVerticalBreak, color = AutoPitchType)) +
geom_point(size = 3) + # Increase point size
labs(title = "Pitch Movement for Aidan Krupp",
x = "Horizontal Break (inches)",
y = "Induced Vertical Break (inches)",
color = "Pitch Type") +
theme_minimal() +
theme(
legend.position = "right",
panel.grid.major = element_line(color = "grey80"),
panel.grid.minor = element_line(color = "grey90"),
axis.text = element_text(color = "black"),
axis.title = element_text(color = "black"),
plot.title = element_text(color = "black"),
legend.background = element_rect(fill = "white", color = NA),
legend.key = element_rect(fill = "white", color = NA),
legend.text = element_text(color = "black"),
legend.title = element_text(color = "black")
)
