# Filter the data for the pitcher Martinez
Martinez_data <- Upper615 %>%
filter(Pitcher == "Martinez, Matthew")
# Create a detailed table for each pitch
detailed_pitch_table <- 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 Martinez")
Detailed Pitch Table for Martinez
| Sinker |
90.32 |
1839.85 |
223.92 |
13.56 |
15.36 |
BallCalled |
6.39 |
0.81 |
4.44 |
7.5 |
| Changeup |
81.63 |
1573.27 |
235.90 |
14.96 |
11.60 |
StrikeCalled |
6.18 |
1.21 |
4.78 |
7.9 |
| Changeup |
81.34 |
1572.57 |
272.03 |
17.91 |
0.86 |
BallCalled |
6.19 |
1.57 |
4.24 |
9.1 |
| Changeup |
82.79 |
1723.18 |
262.43 |
15.85 |
3.51 |
BallCalled |
6.18 |
1.58 |
4.33 |
8.7 |
| Four-Seam |
90.27 |
2045.91 |
199.53 |
6.90 |
20.70 |
BallCalled |
6.33 |
0.95 |
4.55 |
6.7 |
| Four-Seam |
90.03 |
2114.95 |
214.83 |
13.19 |
20.22 |
FoulBallFieldable |
6.37 |
1.04 |
4.23 |
7.2 |
| Curveball |
78.95 |
2468.37 |
52.33 |
-13.36 |
-8.73 |
StrikeCalled |
6.34 |
1.38 |
3.92 |
1.7 |
| Changeup |
81.24 |
1546.99 |
264.34 |
13.29 |
2.70 |
InPlay |
6.21 |
1.61 |
4.12 |
8.8 |
| Four-Seam |
89.89 |
1837.09 |
207.76 |
7.64 |
15.68 |
BallCalled |
6.45 |
1.18 |
4.51 |
6.9 |
| Changeup |
80.91 |
1721.12 |
261.43 |
15.63 |
3.79 |
StrikeSwinging |
6.25 |
1.63 |
4.44 |
8.7 |
| Changeup |
80.52 |
1651.62 |
262.63 |
15.45 |
3.43 |
BallCalled |
6.18 |
1.54 |
4.04 |
8.8 |
| Changeup |
82.02 |
1782.25 |
266.97 |
16.59 |
2.30 |
StrikeCalled |
6.27 |
1.69 |
4.20 |
8.9 |
| Changeup |
81.17 |
1563.85 |
262.68 |
13.18 |
3.10 |
InPlay |
6.16 |
1.68 |
4.18 |
8.8 |
| Changeup |
80.94 |
1560.20 |
261.51 |
16.52 |
3.87 |
StrikeSwinging |
6.22 |
1.22 |
5.06 |
8.7 |
| Changeup |
81.35 |
1769.00 |
258.04 |
16.32 |
4.82 |
InPlay |
6.20 |
1.44 |
5.23 |
8.6 |
| Four-Seam |
90.01 |
2020.38 |
200.71 |
4.11 |
11.99 |
BallCalled |
6.40 |
0.82 |
4.60 |
6.7 |
| Changeup |
80.54 |
1634.54 |
263.72 |
17.78 |
3.36 |
BallCalled |
6.24 |
1.43 |
5.09 |
8.8 |
| Sinker |
88.96 |
2101.56 |
229.15 |
9.46 |
9.32 |
BallCalled |
6.36 |
1.13 |
5.13 |
7.6 |
| Changeup |
82.08 |
1622.94 |
260.69 |
17.50 |
4.28 |
StrikeCalled |
6.24 |
1.55 |
4.35 |
8.7 |
| Sinker |
89.77 |
2172.11 |
223.46 |
8.50 |
10.10 |
BallCalled |
6.45 |
1.29 |
4.66 |
7.4 |
| Changeup |
81.21 |
1665.68 |
259.15 |
17.39 |
4.80 |
BallCalled |
6.23 |
1.45 |
4.45 |
8.6 |
| Four-Seam |
88.62 |
2056.01 |
199.09 |
6.49 |
19.99 |
InPlay |
6.48 |
1.16 |
5.04 |
6.6 |
| Four-Seam |
88.88 |
2008.53 |
202.42 |
5.86 |
15.39 |
FoulBallNotFieldable |
6.42 |
1.15 |
4.94 |
6.7 |
| Changeup |
82.12 |
1700.48 |
258.05 |
20.00 |
5.85 |
StrikeSwinging |
6.18 |
1.69 |
4.04 |
8.6 |
| Changeup |
81.44 |
1593.62 |
255.67 |
20.22 |
6.76 |
BallCalled |
6.12 |
1.56 |
4.08 |
8.5 |
| Changeup |
82.89 |
1665.52 |
254.42 |
20.59 |
7.39 |
StrikeSwinging |
6.19 |
1.66 |
3.99 |
8.5 |
# 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: 26
# Display the summary table
knitr::kable(pitch_summary, caption = "Summary Pitch Table for Martinez")
Summary Pitch Table for Martinez
| Changeup |
61.54% |
16 |
6 |
10 |
37.50% |
62.50% |
81.51 |
1646.68 |
4.53 |
16.82 |
259.98 |
8.7 |
6.20 |
1.53 |
4.41 |
| Curveball |
3.85% |
1 |
0 |
1 |
0.00% |
100.00% |
78.95 |
2468.37 |
-8.73 |
-13.36 |
52.33 |
1.7 |
6.34 |
1.38 |
3.92 |
| Four-Seam |
23.08% |
6 |
3 |
3 |
50.00% |
50.00% |
89.62 |
2013.81 |
17.33 |
7.36 |
204.06 |
6.8 |
6.41 |
1.05 |
4.64 |
| Sinker |
11.54% |
3 |
3 |
0 |
100.00% |
0.00% |
89.68 |
2037.84 |
11.59 |
10.51 |
225.51 |
7.5 |
6.40 |
1.08 |
4.74 |
# 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("Martinez maximum FB velocity: ", max_fb_velocity, "mph\n")
## Martinez maximum FB velocity: 90.32 mph
# Prepare data for plotting pitch locations
pitch_location_data <- 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 Martinez",
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
## mapping: x = 1.75, y = 5, label = LHH
## geom_text: parse = FALSE, check_overlap = FALSE, size.unit = mm, na.rm = FALSE
## stat_identity: na.rm = FALSE
## position_identity
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")
)
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# 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 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")
)
