az-wildcats-vs-UCLA-bruins-Turnovers-Field-goals

az-wildcats-vs-UCLA-bruins-Turnovers-Field-goals.Rmd

---
title: "Visualizing One Million NCAA Basketball Shots"
author: "Max Woolf (@minimaxir)"
date: "2018-03-19"
output:
  html_notebook:
    highlight: tango
    mathjax: null
    number_sections: yes
    theme: spacelab
---

This R Notebook is the complement to my blog post [Visualizing One Million NCAA Basketball Shots](http://minimaxir.com/2018/03/basketball-shots/).

This notebook is licensed under the MIT License. If you use the code or data visualization designs contained within this notebook, it would be greatly appreciated if proper attribution is given back to this notebook and/or myself. Thanks! :)

# Setup

```{r}
library(tidyverse)
library(scales)
library(viridis)
library(extrafont)
library(chron)
library(gganimate)
library(png)
library(gifski)


# Special thanks to Ewen Gallic for his implementation of a ggplot2 basketball court
# http://egallic.fr/en/drawing-a-basketball-court-with-r/
source("bb_court_college.R")

sessionInfo()
```

```{r}
theme_set(theme_minimal(base_size=16, base_family="serif") +
            theme(plot.title = element_text(size=18, family="serif", margin=margin(t = -0.1, b = 0.1, unit='cm')),
                  axis.title.x = element_text(size=16),
                  axis.title.y = element_text(size=16),
                  plot.subtitle = element_text(family="serif", color="#969696", size=12),
                  plot.caption = element_text(size=12, color="#969696"),
                  legend.text = element_text(size = 12),
                  legend.key.width = unit(0.25, unit='cm')))

bb_theme <- theme(
                plot.title = element_text(size=15, family="serif", margin=margin(t = -0.1, b = 0.0, unit='cm')),
                axis.title.x = element_blank(),
                axis.title.y = element_blank(),
                axis.text.x = element_blank(),
                axis.text.y = element_blank(),
                panel.grid = element_blank(),
                
                legend.position = 'top',
                legend.text = element_text(size = 16),
                legend.title = element_text(size = 18),
                legend.key.width = unit(1, unit='cm'),
                legend.key.height = unit(0.25, unit='cm'),
                legend.margin = margin(c(0, 0, -0.4, 0), unit='cm'))
```

```{r}
df <- jsonlite::fromJSON('all.json', flatten = TRUE)

df <- df %>% mutate(
  x = rescale(location.coord_x, to = c(0,94)),
  y = rescale(location.coord_y, to = c(-50,0)),
  time_convert2 = as.POSIXct(strptime(paste0(clock_decimal, ":00"), "%H:%M:%S")),  
  index1 = sequence, 
  fieldgoal_count = 0,
  turnover_count = 0,
  type = event_type
  
)
df <- df[with(df, order(time_convert2)), ]
df <- df[with(df, order(index1)), ]

df 

#count field goals and turnovers
count3 = 0
for (val1 in df$index1){
  count3 = count3+1
  count4 = 0
  count1 = 0
  count2 = 0
for (val in df$index1){

  count4 = count4+1
  
  if(val1 >= val && df$event_type[count4] == 'turnover'){  
    print('turnover')
    print(count4)
    
    count1 = count1+1
    
    
  }
  if(val1 >= val && df$event_type[count4] != 'turnover'){  
    print('field goal')
    print(count4)
      count2 = count2+1
      

  }
  df$turnover_count[count3] = count1
  df$fieldgoal_count[count3]  = count2
}
  
}


df <- rowid_to_column(df,"index11")
df

```

```{r}

plot2 <- P_180 + geom_point(data = df, aes(x = x, y = y, colour = event_type), size = 5, alpha = .8)+   scale_color_manual(values=c("#6868ff", "#ff6868", "#6868ff"), name  ='', breaks=c("turnover", "twopointmade", "threepointmade"),labels=c("Turnover", "Two Points", "Three Points"))+bb_theme + ease_aes()+transition_states(index11,transition_length = 0,
                    state_length = 3,wrap = FALSE) + labs(caption='Arizona Wildcats vs. UCLA Bruins (2/29/2020)',
               title='Wildcat Turnovers: {df$turnover_count[which(df$index11 == closest_state)]}  Wildcat Field Goals: {df$fieldgoal_count[which(df$index11 == closest_state)]}',
                subtitle='{closest_state} : {df$description[which(df$index11 == closest_state)]}')+shadow_mark()


plot2
  

animate(plot2, renderer = gifski_renderer("gganim2.gif") )
animate(plot2, renderer = ffmpeg_renderer(), width = 800, height = 450)
anim_save("turnovers.mp4")


```