# Filter the data for the pitcher Tyler Cox
Brian_Foley_data <- data %>%
filter(Pitcher == "Cox, Tyler")
# Create a detailed table for each pitch
detailed_pitch_table <- Brian_Foley_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 Tyler Cox")
Detailed Pitch Table for Tyler Cox
| Curveball |
73.86 |
2080.58 |
68.49 |
-16.94 |
-4.87 |
StrikeCalled |
4.92 |
2.46 |
5.55 |
2.3 |
| Curveball |
73.52 |
2024.57 |
113.82 |
-10.86 |
6.72 |
FoulBallNotFieldable |
5.15 |
2.46 |
5.48 |
3.8 |
| Curveball |
71.91 |
1914.85 |
43.65 |
-16.07 |
-15.00 |
FoulBallNotFieldable |
5.50 |
1.95 |
5.42 |
1.5 |
| Curveball |
74.01 |
2011.68 |
61.20 |
-12.70 |
-4.88 |
FoulBallNotFieldable |
5.21 |
2.44 |
5.53 |
2.0 |
| Four-Seam |
88.13 |
2024.04 |
220.50 |
11.53 |
14.69 |
StrikeCalled |
5.31 |
2.36 |
6.52 |
7.3 |
| Sinker |
87.61 |
2004.56 |
232.31 |
15.72 |
13.36 |
BallCalled |
5.01 |
2.14 |
6.40 |
7.7 |
| Changeup |
85.54 |
1886.80 |
257.70 |
19.26 |
5.46 |
StrikeCalled |
4.90 |
2.31 |
6.08 |
8.6 |
| Curveball |
73.62 |
1820.50 |
35.88 |
-10.24 |
-12.35 |
InPlay |
5.15 |
2.14 |
5.32 |
1.2 |
| Changeup |
84.65 |
1903.70 |
253.29 |
16.06 |
6.11 |
BallCalled |
5.19 |
2.28 |
6.01 |
8.4 |
| Changeup |
84.82 |
1889.15 |
249.08 |
17.44 |
7.94 |
InPlay |
5.00 |
2.21 |
6.17 |
8.3 |
| Sinker |
86.60 |
1889.16 |
235.70 |
14.06 |
10.75 |
StrikeCalled |
4.90 |
2.39 |
6.12 |
7.9 |
| Sinker |
86.80 |
1877.52 |
238.16 |
13.55 |
9.58 |
BallCalled |
4.95 |
2.20 |
6.01 |
7.9 |
| Changeup |
78.37 |
1931.05 |
258.99 |
21.24 |
5.61 |
BallCalled |
4.76 |
2.43 |
5.70 |
8.6 |
| Changeup |
86.22 |
1862.04 |
264.59 |
13.57 |
2.43 |
InPlay |
4.90 |
2.32 |
6.11 |
8.8 |
| Curveball |
72.10 |
1932.86 |
75.08 |
-11.99 |
-1.33 |
InPlay |
5.06 |
2.47 |
5.64 |
2.5 |
| Changeup |
87.41 |
1929.48 |
250.07 |
17.39 |
7.44 |
BallCalled |
4.96 |
2.22 |
6.14 |
8.3 |
| Changeup |
85.22 |
1828.30 |
248.77 |
17.64 |
8.03 |
StrikeCalled |
5.16 |
2.36 |
6.05 |
8.3 |
| Changeup |
76.69 |
1936.10 |
275.12 |
19.71 |
-0.18 |
InPlay |
4.86 |
2.25 |
5.73 |
9.2 |
# 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 %in% c("BallCalled", "BallinDirt")),
Strikes = sum(!PitchCall %in% c("BallCalled", "BallinDirt")), # 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 Tyler Cox")
Summary Pitch Table for Tyler Cox
| Changeup |
44.44% |
8 |
3 |
5 |
37.50% |
62.50% |
83.61 |
1895.83 |
5.36 |
17.79 |
257.20 |
8.6 |
4.97 |
2.30 |
6.00 |
| Curveball |
33.33% |
6 |
0 |
6 |
0.00% |
100.00% |
73.17 |
1964.17 |
-5.28 |
-13.13 |
66.35 |
2.2 |
5.16 |
2.32 |
5.49 |
| Four-Seam |
5.56% |
1 |
0 |
1 |
0.00% |
100.00% |
88.13 |
2024.04 |
14.69 |
11.53 |
220.50 |
7.3 |
5.31 |
2.36 |
6.52 |
| Sinker |
16.67% |
3 |
2 |
1 |
66.67% |
33.33% |
87.00 |
1923.75 |
11.23 |
14.44 |
235.39 |
7.8 |
4.95 |
2.24 |
6.18 |
# Calculate maximum fastball velocity
max_fb_velocity <- detailed_pitch_table %>%
filter(AutoPitchType %in% c("Four-Seam", "Sinker", "Cutter")) %>%
summarise(MaxFBVelocity = max(ReleaseSpeed, na.rm = TRUE)) %>%
pull(MaxFBVelocity)
# Display the maximum fastball velocity
cat("Tyler Cox maximum FB velocity: ", max_fb_velocity, "mph\n")
## Tyler Cox maximum FB velocity: 88.13 mph
# Prepare data for plotting pitch locations
pitch_location_data <- Brian_Foley_data %>%
select(AutoPitchType, PlateLocHeight, PlateLocSide, PitchCall) %>%
rename(
PitchHeight = PlateLocHeight,
PitchSide = PlateLocSide
) %>%
mutate(
SwingTake = ifelse(PitchCall %in% c("StrikeSwinging", "FoulBall", "FoulBallFieldable", "FoulBallNotFieldable", "InPlay"), "Swing", "Take"),
Chase = ifelse(SwingTake == "Swing" & (PitchSide < -0.85 | PitchSide > 0.85 | 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) +
geom_rect(aes(xmin = -0.5, xmax = 0.5, ymin = 1.75, ymax = 3.25), fill = NA, color = "red", linetype = "solid", size = 1) +
geom_rect(aes(xmin = -0.85, xmax = 0.85, ymin = 1.5, ymax = 3.5), fill = NA, color = "black", linetype = "solid", size = 1) +
geom_rect(aes(xmin = -1.25, xmax = 1.25, ymin = 1.25, ymax = 3.75), fill = NA, color = "gray", linetype = "solid", size = 1) +
scale_x_continuous(limits = c(-2, 2)) +
scale_y_continuous(limits = c(0, 5)) +
coord_fixed(ratio = 1) +
labs(title = "Pitch Locations for Tyler Cox",
x = "Horizontal Location (feet)",
y = "Vertical Location (feet)",
color = "Swing/Take",
shape = "Chase") +
facet_wrap(~ AutoPitchType) +
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
scale_x_continuous(limits = c(-25, 25)) + # Set horizontal limits to +/- 25 inches
scale_y_continuous(limits = c(-25, 25)) + # Set vertical limits to +/- 25 inches
labs(title = paste("Pitch Movement"),
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")
)
