---
title: "Analysis of Spanish play-by-play data"
author: "Guillermo Vinue"
date: "`r Sys.Date()`" 
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Analysis of Spanish play-by-play data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

<!--This document contains all the needed R code to reproduce the results described in the paper *A Web Application for Interactive Visualization of European Basketball Data* ([https://doi.org/10.1089/big.2018.0124](https://doi.org/10.1089/big.2018.0124){target="_blank"}), which presents the dashboard available at [https://www.uv.es/vivigui/AppEuroACB.html](https://www.uv.es/vivigui/AppEuroACB.html){target="_blank"}.-->

This document contains all the needed R code to reproduce the results described in the paper *A Basketball Big Data Platform for Box Score and Play-by-Play Data*, that has been submitted for publication. It presents the dashboard available at [https://www.uv.es/vivigui/AppPBP.html](https://www.uv.es/vivigui/AppPBP.html){target="_blank"}. This dashboard belongs to the platform available at [https://www.uv.es/vivigui/basketball_platform.html](https://www.uv.es/vivigui/basketball_platform.html){target="_blank"}.

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r packages, message=FALSE, eval=FALSE}
# Firstly, load BAwiR and other packages that will be used in the paper:
library(BAwiR) # 1.3
library(tidyverse) # 1.3.2
```

The following data file is an illustration of the type of play-by-play data available from the Spanish ACB league.

```{r data, eval=FALSE}
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)
```

Do some first data processing:

```{r processing, eval=FALSE}
acb_games_2223_sl <- acb_vbc_cz_sl_2223 %>%
  filter(period == "1C")

df1 <- do_prepare_data(df0, day_num, 
                      acb_games_2223_sl, acb_games_2223_info,
                      game_code)
```

```{r lineups, eval=FALSE}
# Lineups and sub-lineups:
data_li <- do_lineup(df1, day_num, game_code, "Valencia Basket", FALSE) 
data_subli <- do_sub_lineup(data_li, 4)
```

```{r possessions, eval=FALSE}
# Possessions:
data_poss <- do_possession(df1, "1C")  
```

```{r timeouts, eval=FALSE}
# Timeouts:
df1_to <- do_prepare_data_to(df0, TRUE, acb_games_2223_info, acb_games_2223_coach)
data_to <- do_time_out_success(df1_to, day_num, game_code, 
                               "Casademont Zaragoza_Porfirio Fisac", FALSE)
```

```{r periods, eval=FALSE}
# Periods:
df0_per <- df0

rm_overtime <- TRUE # Decide if remove overtimes.
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)
                         
data_per <- do_stats_per_period(df3, day_num, game_code, team_sel, period_sel, player_sel)

# Clutch time:
data_clutch <- do_clutch_time(acb_vbc_cz_pbp_2223)
```

```{r fouls, eval=FALSE}
# Free throw fouls:
data_ft_comm <- do_ft_fouls(df0, "comm")
data_ft_rec <- do_ft_fouls(df0, "rec")

# Offensive fouls:
data_off_comm <- do_offensive_fouls(df0, "comm")
data_off_rec <- do_offensive_fouls(df0, "rec")
```

```{r rebounds, eval=FALSE}
# Offensive rebounds:
df1_or <- do_prepare_data_or(df0, TRUE, acb_games_2223_info)
data_or <- do_reb_off_success(df1_or, day_num, game_code, "Valencia Basket", FALSE)
```

```{r session info}
sessionInfo()
```