do_stats_per_period {BAwiR}

Compute stats per period

Description

Compute time played and points scored for a player of interest in any period of the game.

Usage

do_stats_per_period(data, day_num, game_code, team_sel, period_sel, player_sel)

Arguments

data

Prepared data from a given game.

day_num

Day number.

game_code

Game code.

team_sel

One of the teams' names involved in the game.

period_sel

Period of interest. Options can be "xC", where x=1,2,3,4.

player_sel

Player of interest.

Value

Data frame with one row and mainly time played (seconds and minutes) and points scored by the player of interest in the period of interest.

Note

The game_code column allows us to detect the source website, for example, https://jv.acb.com/es/103389/jugadas.

Author(s)

Guillermo Vinue

Examples

library(dplyr)
df0 <- acb_vbc_cz_pbp_2223

day_num <- unique(acb_vbc_cz_pbp_2223$day)
game_code <- unique(acb_vbc_cz_pbp_2223$game_code)

# Remove overtimes:
rm_overtime <- TRUE
if (rm_overtime) {
 df0 <- df0 %>%
   filter(!grepl("PR", period)) %>%
   mutate(period = as.character(period))
}
 
team_sel <- "Valencia Basket" # "Casademont Zaragoza"
period_sel <- "1C"            # "4C"
player_sel <- "Webb"          # "Mara"
 
df1 <- df0 %>%
  filter(team == team_sel) %>%
  filter(!action %in% c("D - Descalificante - No TL", "Altercado no TL")) 
   
df2 <- df1 %>%
  filter(period == period_sel)
   
df0_inli_team <- acb_vbc_cz_sl_2223 %>% 
   filter(team == team_sel, period == period_sel)
 
df3 <- do_prepare_data(df2, day_num, 
                       df0_inli_team, acb_games_2223_info,
                       game_code)
                        
df4 <- do_stats_per_period(df3, day_num, game_code, team_sel, period_sel, player_sel)
#df4