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 Colin Dowlen
Colin_Dowlen_data <- Shore624 %>%
filter(Pitcher == "Dowlen, Colin")
# Create a detailed table for each pitch
detailed_pitch_table <- Colin_Dowlen_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 Colin Dowlen")
Detailed Pitch Table for Colin Dowlen
| Sinker |
87.22 |
2003.31 |
229.64 |
14.89 |
13.83 |
StrikeCalled |
5.19 |
1.98 |
6.09 |
7.7 |
| Curveball |
76.10 |
2998.96 |
58.43 |
-20.25 |
-10.75 |
BallCalled |
5.23 |
2.09 |
5.35 |
1.9 |
| Changeup |
86.18 |
1980.77 |
216.62 |
11.47 |
16.63 |
StrikeSwinging |
5.20 |
2.25 |
5.88 |
7.2 |
| Curveball |
75.41 |
2937.59 |
52.34 |
-18.02 |
-12.21 |
StrikeCalled |
5.21 |
2.15 |
5.21 |
1.7 |
| Changeup |
87.36 |
1980.81 |
231.16 |
14.00 |
12.49 |
BallCalled |
5.07 |
2.00 |
6.04 |
7.7 |
| Sinker |
88.09 |
2052.79 |
222.96 |
14.59 |
16.83 |
StrikeCalled |
5.10 |
2.15 |
6.06 |
7.4 |
| Curveball |
75.61 |
2975.31 |
38.05 |
-13.30 |
-15.31 |
StrikeCalled |
5.29 |
2.08 |
5.37 |
1.3 |
| Sinker |
87.28 |
2042.89 |
240.24 |
16.02 |
10.38 |
BallCalled |
5.25 |
2.03 |
5.48 |
8.0 |
| Changeup |
86.92 |
2006.47 |
233.73 |
15.00 |
12.21 |
BallCalled |
5.09 |
2.05 |
6.01 |
7.8 |
| Four-Seam |
88.08 |
NA |
219.54 |
13.48 |
17.48 |
StrikeCalled |
5.22 |
2.05 |
5.99 |
7.3 |
| Sinker |
88.45 |
2065.82 |
229.50 |
14.32 |
13.42 |
StrikeCalled |
5.22 |
1.92 |
5.98 |
7.7 |
| Four-Seam |
88.10 |
2081.83 |
216.70 |
13.70 |
19.53 |
BallCalled |
5.22 |
1.92 |
6.02 |
7.2 |
| Curveball |
76.62 |
2991.49 |
60.63 |
-17.86 |
-8.51 |
FoulBallNotFieldable |
5.35 |
2.02 |
5.46 |
2.0 |
| Curveball |
76.26 |
2962.42 |
61.61 |
-20.38 |
-9.24 |
StrikeSwinging |
5.10 |
2.14 |
5.65 |
2.1 |
| Sinker |
88.99 |
2062.52 |
227.13 |
15.92 |
16.05 |
FoulBallNotFieldable |
5.23 |
1.88 |
6.01 |
7.6 |
| Sinker |
88.43 |
1945.05 |
223.56 |
13.10 |
14.87 |
BallCalled |
5.29 |
1.87 |
6.08 |
7.5 |
| Curveball |
75.10 |
2834.84 |
55.00 |
-19.05 |
-11.67 |
StrikeCalled |
5.31 |
1.99 |
5.23 |
1.8 |
| Curveball |
75.26 |
2885.98 |
54.01 |
-20.89 |
-13.44 |
InPlay |
5.34 |
2.04 |
5.37 |
1.8 |
# 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 Colin Dowlen")
Summary Pitch Table for Colin Dowlen
| Changeup |
16.67% |
3 |
2 |
1 |
66.67% |
33.33% |
86.82 |
1989.35 |
13.78 |
13.49 |
227.17 |
7.6 |
5.12 |
2.10 |
5.98 |
| Curveball |
38.89% |
7 |
1 |
6 |
14.29% |
85.71% |
75.77 |
2940.94 |
-11.59 |
-18.54 |
54.30 |
1.8 |
5.26 |
2.07 |
5.38 |
| Four-Seam |
11.11% |
2 |
1 |
1 |
50.00% |
50.00% |
88.09 |
2081.83 |
18.51 |
13.59 |
218.12 |
7.2 |
5.22 |
1.98 |
6.00 |
| Sinker |
33.33% |
6 |
2 |
4 |
33.33% |
66.67% |
88.08 |
2028.73 |
14.23 |
14.81 |
228.84 |
7.7 |
5.21 |
1.97 |
5.95 |
# 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("Colin Dowlen maximum FB velocity: ", max_fb_velocity, "mph\n")
## Colin Dowlen maximum FB velocity: 88.99 mph
# Prepare data for plotting pitch locations
pitch_location_data <- Colin_Dowlen_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 Colin Dowlen",
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 Colin Dowlen",
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")
)
