Temperature effects

  • Conventional wisdom: warmer temps -> more home runs.

  • Add in temperature data (included in abdwr3edata package)

  • Also need to focus on outside parks, so include park data (also in package)

temps_parks_2023 <- temps_2023 |> inner_join(parks_2023, by = c("Park"))
sc_2023 <- sc_2023 |> inner_join(temps_parks_2023, by = "game_pk")
temp_hr <- filter(sc_2023, Dome == "No") |> 
  group_by(temperature) |> 
  summarize(
    BIP = n(),
    HR = sum(HR, na.rm = TRUE)
  ) |> 
  mutate(HR_Rate = 100 * HR / BIP)

  • Seems to hold up. A linear fit yields about 0.04% increase per degree (4.65% at 70)