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
Keene614 <- read_excel("C:/Users/Franco Castagliuolo/OneDrive - Bentley University/Neers 24/Pitchers/Keene614/Keene614.xlsx")
# Filter the data for the pitcher Kutz
Kutz_data <- Keene614 %>%
filter(Pitcher == "Kutz, Charlie")
# Create a detailed table for each pitch
detailed_pitch_table <- Kutz_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 Kutz")
Detailed Pitch Table for Kutz
| Sinker |
89.55 |
2283.23 |
99.05 |
-18.65 |
4.17 |
BallCalled |
5.37 |
-2.55 |
6.32 |
3.3 |
| Sinker |
89.30 |
2475.25 |
107.12 |
-18.53 |
7.02 |
BallCalled |
5.40 |
-2.50 |
6.31 |
3.6 |
| Slider |
81.55 |
2696.24 |
309.62 |
7.18 |
-4.59 |
BallCalled |
5.14 |
-2.79 |
5.66 |
10.3 |
| Sinker |
89.20 |
2470.21 |
113.16 |
-16.48 |
8.30 |
StrikeCalled |
5.37 |
-2.50 |
6.27 |
3.8 |
| Slider |
83.92 |
2791.71 |
265.21 |
8.58 |
2.00 |
BallCalled |
5.23 |
-2.73 |
5.66 |
8.8 |
| Sinker |
88.75 |
2429.12 |
110.77 |
-18.34 |
8.25 |
BallCalled |
5.36 |
-2.54 |
6.36 |
3.7 |
| Changeup |
88.38 |
2451.72 |
109.95 |
-20.50 |
8.73 |
BallCalled |
5.37 |
-2.48 |
5.98 |
3.7 |
| Sinker |
89.30 |
2457.39 |
101.81 |
-18.49 |
5.27 |
BallCalled |
5.38 |
-2.53 |
6.45 |
3.4 |
| Sinker |
88.77 |
2386.35 |
106.75 |
-15.83 |
6.12 |
StrikeCalled |
5.33 |
-2.54 |
6.24 |
3.6 |
| Sinker |
89.68 |
2457.08 |
96.34 |
-13.83 |
2.80 |
FoulBallNotFieldable |
5.32 |
-2.55 |
6.13 |
3.2 |
| Slider |
83.82 |
2678.82 |
240.46 |
2.06 |
2.46 |
BallCalled |
5.27 |
-2.60 |
5.77 |
8.0 |
| Changeup |
86.86 |
2427.22 |
120.63 |
-15.27 |
10.39 |
BallCalled |
5.27 |
-2.66 |
6.06 |
4.0 |
| Sinker |
89.16 |
2548.62 |
99.54 |
-17.68 |
4.12 |
InPlay |
5.25 |
-2.58 |
6.30 |
3.3 |
| Sinker |
89.22 |
2338.88 |
100.23 |
-18.58 |
4.59 |
BallinDirt |
5.21 |
-2.59 |
6.20 |
3.3 |
| Sinker |
88.42 |
2372.59 |
90.96 |
-16.08 |
1.49 |
BallCalled |
5.28 |
-2.67 |
6.15 |
3.0 |
# 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\n")
## Total number of pitches thrown: 15
# Display the summary table
knitr::kable(pitch_summary, caption = "Summary Pitch Table for Kutz")
Summary Pitch Table for Kutz
| Changeup |
13.33% |
2 |
2 |
0 |
100.00% |
0.00% |
87.62 |
2439.47 |
9.56 |
-17.88 |
115.29 |
3.9 |
5.32 |
-2.57 |
6.02 |
| Sinker |
66.67% |
10 |
5 |
5 |
50.00% |
50.00% |
89.14 |
2421.87 |
5.21 |
-17.25 |
102.57 |
3.4 |
5.33 |
-2.55 |
6.27 |
| Slider |
20.00% |
3 |
3 |
0 |
100.00% |
0.00% |
83.10 |
2722.26 |
-0.04 |
5.94 |
271.76 |
9.0 |
5.21 |
-2.71 |
5.70 |
# 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("Kutz maximum FB velocity: ", max_fb_velocity, "mph\n")
## Kutz maximum FB velocity: 89.68 mph
# Prepare data for plotting pitch locations
pitch_location_data <- Kutz_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 Kutz",
x = "Horizontal Location (feet)",
y = "Vertical Location (feet)",
color = "Swing/Take",
shape = "Chase") +
facet_wrap(~ AutoPitchType) + # Create individual graphs for each pitch type
geom_text(aes(x = -1.75, y = 5, label = "RHH"), color = "black", size = 3, hjust = 0) + # Label for RHH
geom_text(aes(x = 1.75, y = 5, label = "LHH"), color = "black", size = 3, hjust = 1) + # Label for LHH
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 Kutz",
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")
)
