Plot player names as per the team formations over a football field (well, a green bg)

fifaCharts.R

args <- commandArgs(trailingOnly = TRUE)

library(ggplot2)
library(ggflags)

bg_color = '#5A8E38'


# Declaring constants -----------------------------------------------------

theme_court = function(base_size = 16) {
  theme_bw(base_size) +
    theme(
      text = element_text(color = "#A1BC6A"),
      plot.background = element_rect(fill = bg_color, color = bg_color),
      panel.background = element_rect(fill = bg_color, color = bg_color),
      panel.grid = element_blank(),
      panel.border = element_blank(),
      axis.text = element_blank(),
      axis.title = element_blank(),
      axis.ticks.length = unit(0, "lines"),
      legend.background = element_rect(fill = bg_color, color = bg_color),
      legend.position = "none",
      legend.key = element_blank(),
      legend.text = element_text(size = rel(1.0))
    )
}

goal_keeper <- data.frame(loc_x = c(50), loc_y = c(90), formation = 'goalkeeper')

formation_442 <- data.frame(
  loc_x = c(rep(quantile(seq(
    10:90
  ))[2:5], 2), quantile(seq(10:90))[3] + 1, quantile(seq(10:90))[4] - 1),
  loc_y = c(rep(77, 4), rep(67, 4), rep(57, 2)),
  formation = rep('442', 10)
)

formation_433 <- data.frame(
  loc_x = c(quantile(seq(10:90))[2:5], c(32,52,72) ,c(16,52,86)),
  loc_y = c(rep(77, 4), 65,67,65, rep(57, 3)),
  formation = rep('433', 10)
)

formation_4231 <- data.frame(
  loc_x = c(quantile(seq(10:90))[2:5], quantile(seq(10:90))[3:4] ,c(25,52,75), 52),
  loc_y = c(rep(77, 4), rep(67,2), c(60,62,60), 55),
  formation = rep('4231', 10)
)

formation_4312 <- data.frame(
  loc_x = c(quantile(seq(10:90))[2:5], c(36,52,66) ,52, c(39,63)),
  loc_y = c(rep(77, 4), rep(67,3), c(60), c(55,55)),
  formation = rep('4312', 10)
)


formation_4141 <- data.frame(
  loc_x = c(quantile(seq(10:90))[2:5], 52, c(17,37,65,85) ,52),
  loc_y = c(rep(77, 4), 70, rep(64, 4), 55),
  formation = rep('4141', 10)
)

formation_352 <- data.frame(
  loc_x = c(c(20,50,80), c(15,30,50,70,85) ,c(50,50)),
  loc_y = c(rep(70, 3), 55,40,55,40,55, 30, 15),
  formation = rep('352', 10)
)

all_formations <- dplyr::bind_rows(goal_keeper, formation_442,formation_433,formation_4231,formation_4312,formation_4141,formation_352)


# Create team formation ---------------------------------------------------

create_formation <- function(formation_a, formation_b = NA_character_){
  
  team_a <- all_formations[all_formations$formation == formation_a,]
  team_a <- dplyr::bind_rows(team_a, all_formations[all_formations$formation == 'goalkeeper',])
  team_a$team <- 'team_a'
  team_a$position <- c("Left-Back", "Centre-Back", "Right-Back", "Left Wing", "Left Midfield", "Defensive Midfield", "Right Midfield", "Right Wing", "Attacking Midfield", "Centre-Forward", "Keeper")
  # subs <- c("Central Midfield", "Secondary Striker")
  
  # team_b <- all_formations[all_formations$formation == formation_b,]
  # team_b <- dplyr::bind_rows(team_b, all_formations[all_formations$formation == 'goalkeeper',])
  # team_b$loc_y <- 100 - team_b$loc_y
  # team_b$team <- 'team_b'
  # 
  # formation_df <- dplyr::bind_rows(team_a, team_b)
  # return(formation_df)
  return(team_a)
}


# Create team plots -------------------------------------------------------

create_team_plot <- function(team_type, all_team){
  formation_df <- create_formation('352')
  if(team_type == 'y'){
    team_young <- all_team[all_team$type == 'youngest',]
    team_young$team_name <- c("Nigeria", "Mexico", "Morocco", "Serbia", "Nigeria", "Uruguay", "France", "Panama", "Australia","Morocco","Senegal","Argentina","Panama")
    team_young$team_code <- c("ng", "mx", "ma", "rs", "ng", "uy", "fr", "pa", "au","ma","sn","ar","pa")
    formation_df <- dplyr::left_join(formation_df, team_young, by='position')
  } else {
    team_senior <- all_team[all_team$type == 'senior_most',]
    team_senior$team_name <- c("Egypt", "Mexico", "Australia", "Panama", "Russia", "Portugal", "Switzerland", "Japan", "Spain","Costa Rica","Colombia","Egypt","Poland")
    team_senior$team_code <- c("eg", "mx", "au", "pa", "rs", "pt", "ch", "jp", "es","cr","co","eg","pl")
    formation_df <- dplyr::left_join(formation_df, team_senior, by='position')
  }
  
  empty_court <- ggplot(data = formation_df,
                        aes(x = loc_x, y = loc_y,country=team_code,size=10,
                            label=name)) + geom_rect(aes(xmin = 0, xmax = 100, ymin = 0, ymax = 100), fill = NA, colour = "#000000", size = 1) +
    # geom_rect(aes(xmin = 0, xmax = 100, ymin = 0, ymax = 50), fill = NA, colour = "#000000", size = 1) +
    # geom_rect(aes(xmin = 21, xmax = 79, ymin = 17, ymax = 0), fill = NA, colour = "#000000", size = 1) +
    geom_rect(aes(xmin = 21, xmax = 79, ymin = 83, ymax = 100), fill = NA, colour = "#000000", size = 1) +
    # geom_rect(aes(xmin = 36.8, xmax = 63.2, ymin = 0, ymax = 6), fill = NA, colour = "#000000", size = 1) +
    geom_rect(aes(xmin = 36.8, xmax = 63.2, ymin = 100, ymax = 94), fill = NA, colour = "#000000", size = 1) +
    theme(rect = element_blank(), 
          line = element_blank(), 
          text = element_blank()) + theme_court()
  
  # formation <- empty_court +
  #   geom_point(
  #     alpha = 0.8, size = 4
  #   ) + geom_text(colour = "#000000", aes(label=ifelse(loc_y < 50, formation, '')),hjust=0.5, vjust=-1.2,alpha = 0.8) +
  #   geom_point(
  #     alpha = 0.8, size = 4
  #   ) + geom_text(colour = "#000000", aes(label=ifelse(loc_y > 50, formation, '')),hjust=0.5, vjust=1.8,alpha = 0.8)
  
  formation <- empty_court +
    geom_flag() + 
    scale_country() + 
    geom_text(check_overlap = TRUE, aes(hjust=0.5, vjust=2)) + theme_court()
  
  
  # browser()
  # print(formation)
  
  ggsave(
    plot = formation,width = 6,height = 6,
    filename = glue::glue("team_type_{team_type}.png"),
    device = png(),
    path = "/tmp"
  )
}


# Get position wise young/old player info ---------------------------------

get_position_stats <- function(all_players, type){
  all_players_data <<- read.csv(all_players)
  
  # These players are present in the dataset but they did not participate in FIFA 2018
  
  all_players_data <-
    all_players_data[!all_players_data$name %in% c(
      "Sebastian Szymanski",
      "Hamza Mendyl",
      "Noussair Mazraoui",
      "Karim Hafez",
      "Szymon Zurkowski",
      "Ólafur Ingi Skúlason",
      "Michael Krohn-Dehli",
      "Farid Díaz"
    ),] 
  
  find_players <- function(playerPosition){
    players <- all_players_data[all_players_data$position == playerPosition,]
    youngest <- players[which(players$age == min(players$age)),]
    seniorMost <- players[which(players$age == max(players$age)),]
    return(list(youngest=youngest,seniorMost=seniorMost))
  }
  
  unique_positions <- unique(all_players_data$position)  
  x <- purrr::map(unique_positions, find_players)
  youngest <- dplyr::bind_rows(lapply(x,"[[","youngest"))
  youngest$type <- 'youngest'
  senior_most <- dplyr::bind_rows(lapply(x,"[[","seniorMost"))
  senior_most$type <- 'senior_most'
  all_team <- dplyr::bind_rows(youngest, senior_most)
  
  print(dim(all_team))
  # write.csv(youngest,"/tmp/youngest_team.csv", row.names=F)
  # write.csv(senior_most,"/tmp/senior_team.csv", row.names=F)
  
  create_team_plot(type, all_team)
  
  if(type == 'y'){
    return(youngest)  
  } else if(type == 'o'){
    return(senior_most)  
  } else {
    print("Enter [y]oung/[o]ld")
  }
  }


# Calling the function ----------------------------------------------------

# get_position_stats(all_players = "/tmp/all_players_age.csv", type = "o")

get_position_stats(all_players = args[1], type = args[2])