SLGplot.R

# pitch/play data scraped with pitchRx

pitches18 %>% 
  filter(type == 'X', 
         pitch_type == "FF") %>%
  mutate(TB = case_when(
    event == "Single" ~    1,
    event == "Double" ~    2,
    event == "Triple" ~    3,
    event == "Home Run" ~  4,
    TRUE ~                 0 
  )) %>%
  group_by(start_speed) %>%
  summarize(SLG = mean(TB),
            pitches = n()) %>%
  filter(start_speed < 100,
         start_speed > 90) %>%
  ggplot(aes(start_speed, SLG, size = pitches)) + 
  geom_point() + 
  geom_smooth(method = 'lm', se = FALSE) +
  guides(size = guide_legend(override.aes = list(linetype = 0))) +
  labs(title = "SLG vs. Velocity, 2018",
       subtitle = "(4-seam fastballs, balls in play)") +
  theme_bw()