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 Matthew Martinez
Matthew_Martinez_data <- Shore624 %>%
filter(Pitcher == "Martinez, Matthew")
# Create a detailed table for each pitch
detailed_pitch_table <- Matthew_Martinez_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 Matthew Martinez")
Detailed Pitch Table for Matthew Martinez
| Changeup |
77.16 |
1637.24 |
246.37 |
15.79 |
8.67 |
StrikeCalled |
6.23 |
1.40 |
4.01 |
8.2 |
| Changeup |
77.68 |
1649.49 |
253.18 |
17.75 |
7.07 |
StrikeSwinging |
6.23 |
1.66 |
3.88 |
8.4 |
| Changeup |
87.58 |
1864.50 |
208.11 |
8.85 |
17.98 |
BallCalled |
6.58 |
1.06 |
3.96 |
6.9 |
| Changeup |
77.70 |
1727.86 |
244.17 |
15.73 |
9.38 |
InPlay |
6.22 |
1.60 |
3.78 |
8.1 |
| Curveball |
76.31 |
2469.33 |
43.22 |
-9.26 |
-8.19 |
StrikeCalled |
6.40 |
1.51 |
3.87 |
1.4 |
| Changeup |
77.23 |
1427.00 |
260.73 |
14.04 |
3.99 |
StrikeCalled |
6.15 |
1.60 |
4.07 |
8.7 |
| Curveball |
76.89 |
2492.24 |
21.92 |
-5.88 |
-12.98 |
BallCalled |
6.39 |
1.21 |
3.79 |
0.7 |
| Changeup |
88.47 |
1837.97 |
212.60 |
8.48 |
14.61 |
FoulBallNotFieldable |
6.47 |
0.86 |
4.43 |
7.1 |
| Curveball |
76.33 |
2417.12 |
41.37 |
-9.85 |
-9.51 |
FoulBallNotFieldable |
6.39 |
1.31 |
3.78 |
1.4 |
| Changeup |
78.72 |
1614.57 |
257.30 |
14.73 |
5.00 |
InPlay |
6.22 |
1.45 |
4.15 |
8.6 |
| Changeup |
79.86 |
1849.67 |
244.49 |
17.68 |
10.02 |
StrikeCalled |
6.30 |
1.48 |
4.03 |
8.1 |
| Four-Seam |
88.83 |
1989.35 |
204.04 |
7.99 |
19.14 |
BallCalled |
6.51 |
1.00 |
4.37 |
6.8 |
| Curveball |
75.59 |
2370.72 |
36.23 |
-7.91 |
-9.21 |
BallCalled |
6.29 |
1.37 |
4.01 |
1.2 |
| Changeup |
79.60 |
1608.95 |
252.92 |
14.87 |
6.13 |
FoulBallNotFieldable |
6.19 |
1.50 |
4.07 |
8.4 |
| Changeup |
78.86 |
1697.61 |
251.74 |
14.96 |
6.46 |
FoulBallNotFieldable |
6.17 |
1.73 |
4.13 |
8.4 |
| Curveball |
77.42 |
2474.29 |
36.66 |
-8.88 |
-10.37 |
FoulBallNotFieldable |
6.30 |
1.57 |
3.86 |
1.2 |
| Changeup |
88.21 |
1873.61 |
222.12 |
12.12 |
14.69 |
FoulBallNotFieldable |
6.41 |
1.16 |
4.14 |
7.4 |
| Changeup |
79.93 |
1710.04 |
256.02 |
13.88 |
4.97 |
BallCalled |
6.25 |
1.53 |
4.20 |
8.5 |
| Changeup |
79.89 |
1723.44 |
261.51 |
15.57 |
3.84 |
StrikeSwinging |
6.28 |
1.45 |
4.23 |
8.7 |
# 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: 19
# Display the summary table
knitr::kable(pitch_summary, caption = "Summary Pitch Table for Matthew Martinez")
Summary Pitch Table for Matthew Martinez
| Changeup |
68.42% |
13 |
2 |
11 |
15.38% |
84.62% |
80.84 |
1709.38 |
8.68 |
14.19 |
243.94 |
8.1 |
6.28 |
1.42 |
4.08 |
| Curveball |
26.32% |
5 |
2 |
3 |
40.00% |
60.00% |
76.51 |
2444.74 |
-10.05 |
-8.36 |
35.88 |
1.2 |
6.35 |
1.39 |
3.86 |
| Four-Seam |
5.26% |
1 |
1 |
0 |
100.00% |
0.00% |
88.83 |
1989.35 |
19.14 |
7.99 |
204.04 |
6.8 |
6.51 |
1.00 |
4.37 |
# 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("Matthew Martinez maximum FB velocity: ", max_fb_velocity, "mph\n")
## Matthew Martinez maximum FB velocity: 88.83 mph
# Prepare data for plotting pitch locations
pitch_location_data <- Matthew_Martinez_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 Matthew Martinez",
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 Matthew Martinez",
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")
)
