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
Bristol621 <- read_excel("C:/Users/Franco Castagliuolo/OneDrive - Bentley University/Neers 24/Pitchers/Bristol 621/Bristol 621.xlsx")
# Filter the data for the pitcher Keevan
Keevan_data <- Bristol621 %>%
filter(Pitcher == "Keevan, Josh")
# Create a detailed table for each pitch
detailed_pitch_table <- Keevan_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 Keevan")
Detailed Pitch Table for Keevan
| Changeup |
76.37 |
1773.21 |
114.25 |
-16.35 |
8.83 |
BallCalled |
4.98 |
-1.22 |
6.34 |
3.8 |
| Changeup |
81.49 |
2173.21 |
128.05 |
-17.78 |
15.26 |
BallCalled |
5.23 |
-0.87 |
6.39 |
4.3 |
| Splitter |
84.06 |
2182.58 |
140.79 |
-14.13 |
18.57 |
BallCalled |
5.28 |
-0.71 |
6.56 |
4.7 |
| Changeup |
83.98 |
2264.15 |
128.51 |
-18.23 |
15.79 |
BallCalled |
5.29 |
-0.70 |
6.46 |
4.3 |
| Changeup |
81.01 |
2239.81 |
136.00 |
-15.03 |
16.94 |
StrikeCalled |
5.06 |
-0.88 |
6.43 |
4.5 |
| Curveball |
73.13 |
1992.55 |
279.97 |
4.08 |
1.19 |
BallCalled |
4.79 |
-1.17 |
5.85 |
9.3 |
| Changeup |
81.69 |
2102.58 |
135.19 |
-15.54 |
16.92 |
BallCalled |
5.17 |
-0.77 |
6.55 |
4.5 |
| Curveball |
71.29 |
1953.72 |
262.31 |
2.77 |
2.14 |
StrikeCalled |
4.88 |
-1.10 |
5.74 |
8.7 |
| Changeup |
81.72 |
2181.68 |
135.95 |
-16.09 |
17.95 |
BallCalled |
5.24 |
-0.76 |
6.61 |
4.5 |
| Curveball |
71.87 |
2174.69 |
296.25 |
5.63 |
-1.15 |
FoulBallNotFieldable |
4.96 |
-1.01 |
5.83 |
9.9 |
| Curveball |
73.06 |
2071.09 |
326.55 |
2.60 |
-2.15 |
BallCalled |
4.97 |
-0.94 |
6.06 |
10.9 |
| Changeup |
85.03 |
2185.58 |
132.31 |
-17.29 |
16.99 |
StrikeCalled |
5.18 |
-0.78 |
6.43 |
4.4 |
# 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: 12
# Display the summary table
knitr::kable(pitch_summary, caption = "Summary Pitch Table for Keevan")
Summary Pitch Table for Keevan
| Changeup |
58.33% |
7 |
5 |
2 |
71.43% |
28.57% |
81.61 |
2131.46 |
15.53 |
-16.62 |
130.04 |
4.3 |
5.16 |
-0.85 |
6.46 |
| Curveball |
33.33% |
4 |
2 |
2 |
50.00% |
50.00% |
72.34 |
2048.01 |
0.01 |
3.77 |
291.27 |
9.7 |
4.90 |
-1.05 |
5.87 |
| Splitter |
8.33% |
1 |
1 |
0 |
100.00% |
0.00% |
84.06 |
2182.58 |
18.57 |
-14.13 |
140.79 |
4.7 |
5.28 |
-0.71 |
6.56 |
# 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("Keevan maximum FB velocity: ", max_fb_velocity, "mph\n")
## Keevan maximum FB velocity: -Inf mph
# Prepare data for plotting pitch locations
pitch_location_data <- Keevan_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 Keevan",
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 Keevan",
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")
)
