R/run_expectancy_code.R

In Fackz/baseball: Functions for acquiring and analyzing baseball data

#' Generate run expectancy and related measures and variables from Baseball Savant data
#'
#' These functions allow a user to generate run expectancy and related measures and variables from Baseball Savant data. Measures and variables will be added to the data frame and a run expectancy table will be assigned to the Global Environment.
#' @param df A data frame generated from Baseball Savant.
#' @param level Whether you want run expectancy calculated at the plate appearance or pitch level. Defaults to plate appearance.
#' @keywords MLB, sabermetrics
#' @importFrom dplyr filter group_by summarise arrange lead mutate left_join
#' @importFrom stringr str_count
#' @export
#' @examples
#' \dontrun{run_expectancy_code(df, level = "plate appearances")}

run_expectancy_code <- function(df, level = "plate appearance") {

  single_outs <- c("strikeout", "caught_stealing_2b",
                   "pickoff_caught_stealing_2b", "other_out",
                   "caught_stealing_3b", "caught_stealing_home",
                   "field_out", "force_out", "pickoff_1b",
                   "batter_interference", "fielders_choice",
                   "pickoff_2b", "pickoff_caught_stealing_3b",
                   "pickoff_caught_stealing_home")
  df <- df %>%
    dplyr::arrange(game_pk, at_bat_number, pitch_number) %>%
    dplyr::group_by(game_pk) %>%
    dplyr::mutate(final_pitch_game =
                    ifelse(pitch_number == max(pitch_number), 1, 0)) %>%
    dplyr::ungroup() %>%
    dplyr::group_by(game_pk, at_bat_number, inning_topbot) %>%
    dplyr::mutate(final_pitch_at_bat = ifelse(pitch_number == max(pitch_number), 1, 0)) %>%
    dplyr::ungroup()

  df <- df %>%
    dplyr::arrange(game_pk, inning_topbot, at_bat_number, pitch_number) %>%
    dplyr::mutate(runs_scored_on_pitch = stringr::str_count(des, "scores"),
                  runs_scored_on_pitch =
                    ifelse(events == "home_run", runs_scored_on_pitch + 1,
                           runs_scored_on_pitch),
                  bat_score_after = bat_score + runs_scored_on_pitch) %>%
    dplyr::arrange(game_pk, at_bat_number, pitch_number) %>%
    dplyr::mutate(final_pitch_inning =
                    ifelse(final_pitch_at_bat == 1 &
                             inning_topbot != lead(inning_topbot), 1, 0),
                  final_pitch_inning = ifelse(is.na(final_pitch_inning),
                                              1, final_pitch_inning))

  if (level == "plate appearance") {
    df <- df %>%
      dplyr::group_by(game_pk, inning, inning_topbot) %>%
      dplyr::mutate(bat_score_start_inning = min(bat_score),
                    bat_score_end_inning = max(bat_score),
                    cum_runs_in_inning = cumsum(runs_scored_on_pitch),
                    runs_to_end_inning = bat_score_end_inning - bat_score) %>%
      dplyr::ungroup() %>%
      dplyr::mutate(base_out_state = paste(outs_when_up, " outs, ",
                                           ifelse(!is.na(.$on_1b), "1b", "_"),
                                           ifelse(!is.na(.$on_2b), "2b", "_"),
                                           ifelse(!is.na(.$on_3b), "3b", "_")))

    re_table <- run_expectancy_table(df)

    df <- df %>%
      left_join(re_table, by = "base_out_state")

    df <- df %>%
      dplyr::filter(final_pitch_at_bat == 1) %>%
      dplyr::arrange(game_pk, inning, inning_topbot) %>%
      dplyr::group_by(game_pk, inning, inning_topbot) %>%
      dplyr::mutate(next_base_out_state = dplyr::lead(base_out_state)) %>%
      dplyr::ungroup() %>%
      dplyr::left_join(re_table,
                       by = c("next_base_out_state" = "base_out_state")) %>%
      dplyr::rename(next_avg_re = avg_re.y,
                    avg_re = avg_re.x) %>%
      dplyr::mutate(next_avg_re = ifelse(is.na(next_avg_re), 0, next_avg_re),
                    change_re = next_avg_re - avg_re,
                    re24 = change_re + runs_scored_on_pitch) %>%
      dplyr::arrange(game_pk, inning, inning_topbot)
  } else {
    df <- df %>%
      dplyr::group_by(game_pk, inning, inning_topbot) %>%
      dplyr::mutate(bat_score_start_inning = min(bat_score),
                    bat_score_end_inning = max(bat_score),
                    cum_runs_in_inning = cumsum(runs_scored_on_pitch),
                    runs_to_end_inning = bat_score_end_inning - bat_score) %>%
      dplyr::ungroup() %>%
      dplyr::mutate(count_base_out_state =
                      paste(balls, "-", strikes, ", ",
                            outs_when_up, " outs, ",
                            ifelse(!is.na(.$on_1b), "1b", "_"),
                            ifelse(!is.na(.$on_2b), "2b", "_"),
                            ifelse(!is.na(.$on_3b), "3b", "_")))

    re_table <- run_expectancy_table(df, level = "pitch")

    df <- df %>%
      left_join(re_table, by = "count_base_out_state")

    df <- df %>%
      #dplyr::filter(final_pitch_at_bat == 1) %>%
      dplyr::arrange(game_pk, inning, inning_topbot) %>%
      dplyr::group_by(game_pk, inning, inning_topbot) %>%
      dplyr::mutate(next_count_base_out_state =
                      dplyr::lead(count_base_out_state)) %>%
      dplyr::ungroup() %>%
      dplyr::left_join(re_table,
                       by = c("next_count_base_out_state" =
                                "count_base_out_state")) %>%
      dplyr::rename(next_avg_re = avg_re.y,
                    avg_re = avg_re.x) %>%
      dplyr::mutate(next_avg_re = ifelse(is.na(next_avg_re), 0, next_avg_re),
                    change_re = next_avg_re - avg_re,
                    re24 = change_re + runs_scored_on_pitch) %>%
      dplyr::arrange(game_pk, inning, inning_topbot)
  }

  assign("run_expectancy_state_table", re_table, envir = .GlobalEnv)

  df

}