Quarto document showing work for Zack Wheeler 2023 NLCS work

Wheeler_Work.qmd

---
title: "Zach Wheeler 2023 NCS"
format: html
editor: visual
---

Load in necessary packages:

```{r}
library(baseballr)
library(dplyr)
library(ggplot2)
library(janitor)
```

Also need this helper function when we plot pitch locations:

```{r}
add_zone <- function(Color = "red"){
  topKzone <- 3.5
  botKzone <- 1.6
  inKzone <- -0.85
  outKzone <- 0.85
  kZone <- data.frame(
    x=c(inKzone, inKzone, outKzone, outKzone, inKzone),
    y=c(botKzone, topKzone, topKzone, botKzone, botKzone)
  )
  geom_path(aes(.data$x, .data$y), data=kZone,
              lwd=1, col=Color)
}
```

Read in playoff data for two days:

```{r}
day1 <- statcast_search("2023-10-16", "2023-10-16")
day2 <- statcast_search("2023-10-21", "2023-10-21")
```

Focus on pitches thrown by Wheeler (statcast id 554430):

```{r}
zw <- rbind(day1, day2) |> 
     filter(pitcher == 554430)
```

Table of pitches thrown each game:

```{r}
table(zw$game_date)
```

What types of pitches were thrown each game?

```{r}
tabyl(zw, game_date, pitch_name) |> 
  adorn_percentages()
```

Outcomes of each pitch type?

```{r}
tabyl(zw, description, pitch_name) 
```


Outcomes of balls put into play?

First define Hit variable:

```{r}
hits <- c("single", "double", "triple", "home_run")
zw |> 
  mutate(Hit = ifelse(events %in% hits, "YES", "NO")) ->
  zw
```

Graph of launch variables where color of point corresponds to outcome:

```{r}
ggplot(filter(zw, type == "X"), 
       aes(launch_angle, launch_speed,
           color = Hit)) +
  geom_point() + 
  geom_point(data = filter(zw, events == "home_run"),
             size = 5) +
  theme(text=element_text(size=18)) +
  theme(plot.title = element_text(colour = "blue", size = 18,
                                  hjust = 0.5, vjust = 0.8, angle = 0)) +
  ggtitle("Launch Variables for BIP - Zack Wheeler's 2023 NLCS")
```


Define count and number of pitch variables:

```{r}
zw |> 
  mutate(Count = paste(balls, strikes, sep = "-"),
         N_Pitch = balls + strikes + 1 ) -> zw
```


Look at frequencies of count after each pitch 

```{r}
tabyl(zw, N_Pitch, Count)
```

Put counts in a data frame suitable for graphing:

```{r}
df <- data.frame(N_Pitch = c(1, 1, 2, 2, 2, 3, 3, 4, 4, 5),
                 Count = c("0-1", "1-0", "0-2", "1-1", "2-0", "1-2", "2-1",
                           "2-2", "3-1", "3-2"),
                 Advantage = c(1, -1, 2, 0, -2, 1, -1, 0, -2, -1),
                 N = c(31, 12, 17, 19, 2, 18, 9, 14, 2, 7))
```

```{r}
ggplot(df, aes(N_Pitch, Advantage, label = Count,
               size = N)) +
  geom_label(color = "white", fill = "red") +
  ggtitle("Zack Wheeler's Counts for the 2023 NLCS") +
  theme(text=element_text(size=18)) +
  labs(y = "Pitcher Advantage",
       x = "# of Pitches") +
  theme(plot.title = element_text(colour = "blue", size = 18,
                                  hjust = 0.5, vjust = 0.8, angle = 0))
```



Relationship between count and launch speed?

```{r}
ggplot(filter(zw, type == "X"),
       aes(launch_speed, Count)) +
  geom_point() +
  theme(text=element_text(size=18))
```

Count and estimated batting average?

```{r}
ggplot(filter(zw, type == "X"),
       aes(estimated_ba_using_speedangle, Count)) +
  geom_point() +
  theme(text=element_text(size=18)) +
  ggtitle("Relationship Between Estimated BA and Count") +
  theme(plot.title = element_text(colour = "blue", size = 18,
                                  hjust = 0.5, vjust = 0.8, angle = 0))
```

Pitch locations:

```{r}
ggplot(zw, aes(plate_x, plate_z,
               color = description)) +
  geom_point() +
  add_zone("black") +
  facet_wrap(~ pitch_name, ncol = 3) +
  theme(aspect.ratio = 1) +
  theme(text=element_text(size=18)) +
  ggtitle("Pitch Locations for Each Pitch Type") +
  theme(plot.title = element_text(colour = "blue", size = 18,
                                  hjust = 0.5, vjust = 0.8, angle = 0))
```


Some of these location patterns are better understood by exploring association between pitch type and batter side:

```{r}
tabyl(zw, stand, pitch_name)
```