Stanton.R

library(baseballr)
library(dplyr)
library(BayesTestStreak)
library(BApredict)
library(TeachBayes)

# read in batter log data for Stanton for 2017 season
playerid_lookup("Stanton")
stanton <- scrape_statcast_savant_batter("2017-03-25", 
                              "2017-08-15", 519317)

# get sequence of HR outcomes (1 or 0) for each of Stanton's PA's
s2 <- filter(stanton, is.na(events) == FALSE)
s3 <- arrange(s2, game_date, at_bat_number)
y <- ifelse(s3$events == "home_run", 1, 0)

# define a theme for the graph title
TH <- theme(plot.title = element_text(colour = "blue", size = 18, 
                                      hjust = 0.5, vjust = 0.8, angle = 0))

# rug plot nad moving average plot
plot_streak_data(y) + ggtitle("Stanton Sequence of 2017 Home Runs") + 
  TH + xlab("Plate Appearance")
mavg_plot(y, 30) + 
  ggtitle("Moving Average of Home Run Rates - Window of 30 PAs") + TH

# how many hr will he hit in remaining games?
d <- collect_hitting_data()
p <- predict_hr(d, "Stanton")
bar_plot(p$future_HR) + TH + 
  ggtitle("Predictive Distribution of Number of Future Home Runs")