do_stats_per_period: Compute stats per period

In BAwiR: Analysis of Basketball Data

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

BAwiR documentation built on Nov. 14, 2023, 5:08 p.m.