R/game_viz.r
In EFastner/icescrapR: A package for scraping and summarizing PbP Data from NHL.com
Defines functions
viz_team_summary
viz_corsi_positions
viz_corsi_graph
viz_draw_rink
Documented in
viz_corsi_graph
viz_corsi_positions
viz_draw_rink
viz_team_summary
#'Visual Representation of Hockey Rink
#'
#'Create a visual representation of a hockey rink for use with ggplot2
#'
#'@author Prashanth Iyer (Twitter: \href{https://twitter.com/iyer_prashanth}{@@iyer_prashanth})
#'@export
viz_draw_rink <- function() {
################################################################################
##This code written by Prashanth Iyer who can be found on twitter #####
##@iyer_prashanth and is a really good follow #####
################################################################################
xseq <- seq(-4, 4, length = 100)
theta1 <- seq(0, 2 * pi, length = 300)
theta <- seq(0, 2 * pi, length = 300)
dd <- (5 + 7 / 12) / 2
## Blank NHL Rink
rink <- ggplot2::ggplot(data = data.frame(x = 1, y = 1), aes(x, y)) +
ggplot2::geom_path(data = data.frame(
x = c(15, 87 + 13 * sin(seq(0, pi / 2, length = 20)),
87 + 13 * sin(seq(pi / 2, 0, length = 20)), 15),
y = c(-42.5, -42.5 + 15 - 15 * cos(seq(0, pi / 2, length = 20)),
42.5 - 15 + 15 * cos(seq(pi / 2, 0, length = 20)), 42.5))) +
ggplot2::geom_path(data = data.frame(
x = c(15, -87 - 13 * sin(seq(0, pi / 2, length = 20)),
-87 - 13 * sin(seq(pi / 2, 0, length = 20)), 15),
y = c(-42.5, -42.5 + 15 - 15 * cos(seq(0, pi / 2, length = 20)),
42.5 - 15 + 15 * cos(seq(pi / 2, 0, length = 20)), 42.5))) +
## Goal Lines
ggplot2::geom_path(data = data.frame(x = c(89),
y = c(42.5 - 15 + sqrt(15^2 - (15 - 11)^2),
-(42.5 - 15 + sqrt(15^2 - (15 - 11)^2)))),
color = 'red') +
ggplot2::geom_path(data = data.frame(x = c(-89),
y = c(42.5 - 15 + sqrt(15^2 - (15 - 11)^2),
-(42.5 - 15 + sqrt(15^2 - (15 - 11)^2)))),
color = 'red') +
## Nets
ggplot2::geom_path(data = data.frame(x = c(90, 92, 92, 90)), y = c(-3, -3, 3, 3)) +
ggplot2::geom_path(data = data.frame(x = c(-90, -92, -92, -90), y = c(-3,-3, 3, 3))) +
## Restricted Area
ggplot2::geom_segment(aes(x = 89, y = -11, xend = 100, yend = -14), color = 'red') +
ggplot2::geom_segment(aes(x = 89, y = 11, xend = 100, yend = 14), color = 'red') +
ggplot2::geom_segment(aes(x = -89, y = -11, xend = -100, yend = -14), color = 'red') +
ggplot2::geom_segment(aes(x = -89, y = 11, xend =-100, yend = 14), color = 'red') +
## Red Line (Center Ice)
ggplot2::geom_segment(aes(x = 0, y = -42.5, xend = 0, yend = 42.5), color = 'red', size = 1) +
## Blue Lines
ggplot2::geom_segment(aes(x = 25, y = -42.5, xend = 25, yend = 42.5), color = 'blue', size = 1) +
ggplot2::geom_segment(aes(x = -25, y = -42.5, xend = -25, yend = 42.5), color = 'blue', size = 1) +
## Crease
ggplot2::geom_polygon(data = data.frame(x = 1 * c(89, 83+xseq^2 / 4^2 * 1.5, 89),
y = c(-4, xseq, 4)),
color = 'red', fill = 'deepskyblue2') +
ggplot2::geom_polygon(data = data.frame(x = -1 * c(89, 83 + xseq^2 / 4^2 * 1.5, 89),
y = c(-4, xseq, 4)),
color = 'red', fill = 'deepskyblue2') +
## Center Ice Circle
ggplot2::geom_path(data = data.frame(x = 15 * sin(theta1)),
y = 15 * cos(theta1), color = 'deepskyblue2') +
## Faceoff Dots
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = 20 + 1 * sin(theta)),
color = "red", fill = "red") +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = -20 + 1 * sin(theta)),
color = "red", fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = -20 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = 20 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = -69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = 69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = -69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = 69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
## Faceoff Circles
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 - 2,
yend = 22 + 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 + 2,
yend = 22 + 0.75, xend = 69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 - 2,
yend = -22 + 0.75, xend = 69 - 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 + 2,
yend = -22 + 0.75, xend = 69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 - 2,
yend = -22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 + 2,
yend = -22 - 0.75, xend = 69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 + 2,
yend = 22 - 0.75, xend = 69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 - 2,
yend = 22 + 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 - 2,
yend = 22 - 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 + 2,
yend = 22 + 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 - 2,
yend = -22 + 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 + 2,
yend = 22 - 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 + 2,
yend = -22 + 0.75, xend = -69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 - 2,
yend = -22 - 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 + 2,
yend = -22 - 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = 69 - dd,
yend = 22 - 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = 69 + dd,
yend = 22 - 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = 69 + dd,
yend = 22+17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = 69 - dd,
yend = 22 + 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = 69 - dd,
yend = -22 + 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = 69 + dd,
yend = -22 + 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = 69 - dd,
yend = -22 - 17, xend = 69 - dd), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = 69 + dd,
yend = -22 - 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = -69 + dd,
yend = -22 + 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = -69 - dd,
yend = -22 - 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = -69 + dd,
yend = -22 - 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = -69 - dd,
yend = -22 + 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = -69 + dd,
yend = 22 - 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = -69 - dd,
yend = 22 - 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = -69 - dd,
yend = 22 + 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = -69 + dd,
yend = 22 + 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 + 2,
yend = 22 + 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 - 2,
yend = 22 + 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 + 2,
yend = 22 - 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 + 2,
yend = 22 + 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 - 2,
yend = 22 + 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 + 2,
yend = 22 - 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 - 2,
yend = 22 - 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 + 2,
yend = -22 - 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 - 2,
yend = -22 - 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 + 2,
yend = -22 + 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 - 2,
yend = -22 + 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 + 2,
yend = -22 + 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 - 2,
yend = -22 - 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 - 2,
yend = -22 + 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 + 2,
yend = -22 - 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_path(data = data.frame(y = 22 + 15 * cos(theta),
x = 69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = 22 + 15 * cos(theta),
x = -69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = -22 + 15 * cos(theta),
x = -69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = -22 + 15 * cos(theta),
x = 69 + 15 * sin(theta)), color = 'red') +
ggplot2::theme_void() +
ggplot2::coord_fixed()
return(rink)
}
#'Chart Corsi Events for Each Team
#'
#'Create a chart of all corsi events for each team plotted by minute of
#'the game using NHL RTSS data. Only uses one game at a time.
#'
#'@param rawdata NHL RTSS data for a single game
#'@param color_list utilizes the hex colors stored in team_colors$primary unless otherwise specified
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_corsi_graph <- function(rawdata, color_list = team_colors) {
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
#Utilize enhanced_pbp to add more columns
df.enhanced_pbp <- enhanced_pbp(rawdata)
#Filter only corsi events
df.corsi_table <-
dplyr::filter(df.enhanced_pbp, event_type %in% names(corsi_events)) %>%
dplyr::group_by(event_team) %>%
dplyr::mutate(team_corsi = row_number())
#Set Home and Away Teams
home_team <- df.corsi_table[[1,"home_team"]]
away_team <- df.corsi_table[[1,"away_team"]]
viz.corsi_graph <-
ggplot2::ggplot(data = df.corsi_table, mapping = aes(x = game_mins, y = team_corsi)) +
ggplot2::ggtitle(paste("Team Corsi by Minute\n",home_team, " ", max(df.corsi_table$home_score), " vs. ", away_team, " ", max(df.corsi_table$away_score), sep = "")) +
ggplot2::theme(plot.title = element_text(hjust = 0.5)) +
ggplot2::labs(x = "Game Minute", y = "Corsi", shape = "Shot Type", color = "Team") +
ggplot2::geom_line(mapping = aes(color = event_team)) +
ggplot2::geom_point(mapping = aes(shape = event_type, color = event_team), size = 3) +
ggplot2::geom_text(data = subset(df.corsi_table, event_type == "GOAL"), vjust = -1, hjust = 1, nudge_x = 0, mapping = aes(color = event_team, label = event_player_1)) +
#IN DEVELOPMENT - Need to adjust function to end PP after a PP goal and remove Offsetting Penalties
#geom_rect(data = df.penalties, mapping = aes(xmin = game_mins, xmax = pen_end, ymin = -Inf, ymax = Inf, color = team_adv), alpha = .05) +
ggplot2::geom_vline(mapping = aes(xintercept = 20), alpha = .5, linetype = "longdash") +
ggplot2::geom_vline(mapping = aes(xintercept = 40), alpha = .5, linetype = "longdash") +
ggplot2::scale_color_manual(values = df.primary_colors) +
ggplot2::scale_shape_manual(values = corsi_events) +
ggplot2::scale_fill_manual(values = df.primary_colors)
return(viz.corsi_graph)
}
#'Chart Corsi Events and Their Positions
#'
#'Create a visual representation of all corsi events for a given game and their position on the ice
#'
#'@param rawdata NHL RTSS data for a single game
#'@param color_list utilizes the hex colors stored in team_colors$primary unless otherwise specified
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_corsi_positions <- function(rawdata, color_list = team_colors) {
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
#Utilize enhanced_pbp to add more columns
df.enhanced_pbp <- enhanced_pbp(rawdata)
#Filter only corsi events
df.corsi_table <-
dplyr::filter(df.enhanced_pbp, event_type %in% names(corsi_events)) %>%
dplyr::group_by(event_team) %>%
dplyr::mutate(team_corsi = row_number())
#Add Corsi Points
chart.corsi_positions <-
rink +
ggplot2::labs(color = "Team", shape = "Shot Type") +
ggplot2::geom_point(data = filter(df.corsi_table, !is.na(side_coordsx) & !is.na(side_coordsy)),
mapping = aes(x = side_coordsx,
y = side_coordsy,
color = event_team,
shape = event_type),
size = 3) +
ggplot2::scale_color_manual(values = df.primary_colors) +
ggplot2::scale_shape_manual(values = corsi_events)
return(chart.corsi_positions)
}
#'Graphically Summarize Team Stats
#'
#'Create a graphical representation of specific team stats for a given game
#'
#'\itemize{
#' \item Blocks = Total blocks by each team
#' \item Hits = Total hits by each team
#' \item Faceoffs = Total faceoffs won by each team
#' \item Corsi = Total corsi events by each team
#' \item Shots = Total shots by each team
#' \item Goals = Total goals by each team
#'}
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_team_summary <- function(rawdata, color_list = team_colors) {
#DESCRIPTION - Use fun.team_summary to create a vizualization of team game performance
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Set Home and Away Teams
home_team <- rawdata[[1,"home_team"]]
away_team <- rawdata[[1,"away_team"]]
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
df.team_summary <- get_team_stats(rawdata)
chart.team_summary <-
ggplot2::ggplot(data = df.team_summary, mapping = aes(x = factor(Event, levels = c("Blocks", "Hits", "Faceoffs", "Corsi", "Shots", "Goals")),
fill = factor(event_team, levels = c(as.character(away_team),as.character(home_team))),
y = Value)) +
ggplot2::ggtitle(paste("Team Summary")) +
ggplot2::labs(fill = "Team") +
ggplot2::theme(plot.title = element_text(hjust = 0.5),
panel.grid = element_blank(),
panel.background = element_blank(),
axis.ticks = element_blank(),
axis.text.y = element_text(size = 11, color = "black"),
axis.line.x = element_blank(),
axis.text.x = element_blank(),
axis.title = element_blank()) +
ggplot2::geom_col(position = "fill") +
ggplot2::geom_text(data = subset(df.team_summary, event_team == as.character(home_team)), position = position_fill(vjust = -0.025), mapping = aes(label = Value)) +
ggplot2::geom_text(data = subset(df.team_summary, event_team == as.character(away_team)), position = position_fill(vjust = 1.025), mapping = aes(label = Value)) +
ggplot2::geom_hline(yintercept = 0.5, linetype = "longdash", alpha = .75) +
ggplot2::coord_flip() +
ggplot2::scale_fill_manual(values = df.primary_colors)
return(chart.team_summary)
}
EFastner/icescrapR documentation built on Jan. 15, 2022, 1:11 p.m.
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Defines functions viz_team_summary viz_corsi_positions viz_corsi_graph viz_draw_rink
Documented in viz_corsi_graph viz_corsi_positions viz_draw_rink viz_team_summary
#'Visual Representation of Hockey Rink
#'
#'Create a visual representation of a hockey rink for use with ggplot2
#'
#'@author Prashanth Iyer (Twitter: \href{https://twitter.com/iyer_prashanth}{@@iyer_prashanth})
#'@export
viz_draw_rink <- function() {
################################################################################
##This code written by Prashanth Iyer who can be found on twitter #####
##@iyer_prashanth and is a really good follow #####
################################################################################
xseq <- seq(-4, 4, length = 100)
theta1 <- seq(0, 2 * pi, length = 300)
theta <- seq(0, 2 * pi, length = 300)
dd <- (5 + 7 / 12) / 2
## Blank NHL Rink
rink <- ggplot2::ggplot(data = data.frame(x = 1, y = 1), aes(x, y)) +
ggplot2::geom_path(data = data.frame(
x = c(15, 87 + 13 * sin(seq(0, pi / 2, length = 20)),
87 + 13 * sin(seq(pi / 2, 0, length = 20)), 15),
y = c(-42.5, -42.5 + 15 - 15 * cos(seq(0, pi / 2, length = 20)),
42.5 - 15 + 15 * cos(seq(pi / 2, 0, length = 20)), 42.5))) +
ggplot2::geom_path(data = data.frame(
x = c(15, -87 - 13 * sin(seq(0, pi / 2, length = 20)),
-87 - 13 * sin(seq(pi / 2, 0, length = 20)), 15),
y = c(-42.5, -42.5 + 15 - 15 * cos(seq(0, pi / 2, length = 20)),
42.5 - 15 + 15 * cos(seq(pi / 2, 0, length = 20)), 42.5))) +
## Goal Lines
ggplot2::geom_path(data = data.frame(x = c(89),
y = c(42.5 - 15 + sqrt(15^2 - (15 - 11)^2),
-(42.5 - 15 + sqrt(15^2 - (15 - 11)^2)))),
color = 'red') +
ggplot2::geom_path(data = data.frame(x = c(-89),
y = c(42.5 - 15 + sqrt(15^2 - (15 - 11)^2),
-(42.5 - 15 + sqrt(15^2 - (15 - 11)^2)))),
color = 'red') +
## Nets
ggplot2::geom_path(data = data.frame(x = c(90, 92, 92, 90)), y = c(-3, -3, 3, 3)) +
ggplot2::geom_path(data = data.frame(x = c(-90, -92, -92, -90), y = c(-3,-3, 3, 3))) +
## Restricted Area
ggplot2::geom_segment(aes(x = 89, y = -11, xend = 100, yend = -14), color = 'red') +
ggplot2::geom_segment(aes(x = 89, y = 11, xend = 100, yend = 14), color = 'red') +
ggplot2::geom_segment(aes(x = -89, y = -11, xend = -100, yend = -14), color = 'red') +
ggplot2::geom_segment(aes(x = -89, y = 11, xend =-100, yend = 14), color = 'red') +
## Red Line (Center Ice)
ggplot2::geom_segment(aes(x = 0, y = -42.5, xend = 0, yend = 42.5), color = 'red', size = 1) +
## Blue Lines
ggplot2::geom_segment(aes(x = 25, y = -42.5, xend = 25, yend = 42.5), color = 'blue', size = 1) +
ggplot2::geom_segment(aes(x = -25, y = -42.5, xend = -25, yend = 42.5), color = 'blue', size = 1) +
## Crease
ggplot2::geom_polygon(data = data.frame(x = 1 * c(89, 83+xseq^2 / 4^2 * 1.5, 89),
y = c(-4, xseq, 4)),
color = 'red', fill = 'deepskyblue2') +
ggplot2::geom_polygon(data = data.frame(x = -1 * c(89, 83 + xseq^2 / 4^2 * 1.5, 89),
y = c(-4, xseq, 4)),
color = 'red', fill = 'deepskyblue2') +
## Center Ice Circle
ggplot2::geom_path(data = data.frame(x = 15 * sin(theta1)),
y = 15 * cos(theta1), color = 'deepskyblue2') +
## Faceoff Dots
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = 20 + 1 * sin(theta)),
color = "red", fill = "red") +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = -20 + 1 * sin(theta)),
color = "red", fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = -20 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = 20 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = -69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = 22 + 1 * cos(theta),
x = 69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = -69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
ggplot2::geom_polygon(data = data.frame(y = -22 + 1 * cos(theta),
x = 69 + 1 * sin(theta)),
color = 'red', fill = 'red') +
## Faceoff Circles
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 - 2,
yend = 22 + 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 + 2,
yend = 22 + 0.75, xend = 69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 - 2,
yend = -22 + 0.75, xend = 69 - 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 + 2,
yend = -22 + 0.75, xend = 69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 - 2,
yend = -22 - 0.75, xend = 69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 + 2,
yend = -22 - 0.75, xend = 69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 + 2,
yend = 22 - 0.75, xend = 69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 - 2,
yend = 22 + 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 - 2,
yend = 22 - 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 + 2,
yend = 22 + 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 - 2,
yend = -22 + 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 + 2,
yend = 22 - 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 + 2,
yend = -22 + 0.75, xend = -69 + 6), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 - 2,
yend = -22 - 0.75, xend = -69 - 6), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 + 2,
yend = -22 - 0.75, xend = -69 + 6), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = 69 - dd,
yend = 22 - 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = 69 + dd,
yend = 22 - 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = 69 + dd,
yend = 22+17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = 69 - dd,
yend = 22 + 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = 69 - dd,
yend = -22 + 17, xend = 69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = 69 + dd,
yend = -22 + 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = 69 - dd,
yend = -22 - 17, xend = 69 - dd), color= 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = 69 + dd,
yend = -22 - 17, xend = 69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = -69 + dd,
yend = -22 + 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = -69 - dd,
yend = -22 - 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 15, x = -69 + dd,
yend = -22 - 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 15, x = -69 - dd,
yend = -22 + 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = -69 + dd,
yend = 22 - 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 15, x = -69 - dd,
yend = 22 - 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = -69 - dd,
yend = 22 + 17, xend = -69 - dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 15, x = -69 + dd,
yend = 22 + 17, xend = -69 + dd), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 + 2,
yend = 22 + 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = 69 - 2,
yend = 22 + 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 + 2,
yend = 22 - 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = 69 - 2,
yend = 22 - 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 + 2,
yend = 22 + 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 + 0.75, x = -69 - 2,
yend = 22 + 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 + 2,
yend = 22 - 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = 22 - 0.75, x = -69 - 2,
yend = 22 - 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 + 2,
yend = -22 - 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = -69 - 2,
yend = -22 - 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 + 2,
yend = -22 + 3.75, xend = -69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = -69 - 2,
yend = -22 + 3.75, xend = -69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 + 2,
yend = -22 + 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 - 2,
yend = -22 - 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 + 0.75, x = 69 - 2,
yend = -22 + 3.75, xend = 69 - 2), color = 'red') +
ggplot2::geom_segment(aes(y = -22 - 0.75, x = 69 + 2,
yend = -22 - 3.75, xend = 69 + 2), color = 'red') +
ggplot2::geom_path(data = data.frame(y = 22 + 15 * cos(theta),
x = 69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = 22 + 15 * cos(theta),
x = -69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = -22 + 15 * cos(theta),
x = -69 + 15 * sin(theta)), color = 'red') +
ggplot2::geom_path(data = data.frame(y = -22 + 15 * cos(theta),
x = 69 + 15 * sin(theta)), color = 'red') +
ggplot2::theme_void() +
ggplot2::coord_fixed()
return(rink)
}
#'Chart Corsi Events for Each Team
#'
#'Create a chart of all corsi events for each team plotted by minute of
#'the game using NHL RTSS data. Only uses one game at a time.
#'
#'@param rawdata NHL RTSS data for a single game
#'@param color_list utilizes the hex colors stored in team_colors$primary unless otherwise specified
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_corsi_graph <- function(rawdata, color_list = team_colors) {
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
#Utilize enhanced_pbp to add more columns
df.enhanced_pbp <- enhanced_pbp(rawdata)
#Filter only corsi events
df.corsi_table <-
dplyr::filter(df.enhanced_pbp, event_type %in% names(corsi_events)) %>%
dplyr::group_by(event_team) %>%
dplyr::mutate(team_corsi = row_number())
#Set Home and Away Teams
home_team <- df.corsi_table[[1,"home_team"]]
away_team <- df.corsi_table[[1,"away_team"]]
viz.corsi_graph <-
ggplot2::ggplot(data = df.corsi_table, mapping = aes(x = game_mins, y = team_corsi)) +
ggplot2::ggtitle(paste("Team Corsi by Minute\n",home_team, " ", max(df.corsi_table$home_score), " vs. ", away_team, " ", max(df.corsi_table$away_score), sep = "")) +
ggplot2::theme(plot.title = element_text(hjust = 0.5)) +
ggplot2::labs(x = "Game Minute", y = "Corsi", shape = "Shot Type", color = "Team") +
ggplot2::geom_line(mapping = aes(color = event_team)) +
ggplot2::geom_point(mapping = aes(shape = event_type, color = event_team), size = 3) +
ggplot2::geom_text(data = subset(df.corsi_table, event_type == "GOAL"), vjust = -1, hjust = 1, nudge_x = 0, mapping = aes(color = event_team, label = event_player_1)) +
#IN DEVELOPMENT - Need to adjust function to end PP after a PP goal and remove Offsetting Penalties
#geom_rect(data = df.penalties, mapping = aes(xmin = game_mins, xmax = pen_end, ymin = -Inf, ymax = Inf, color = team_adv), alpha = .05) +
ggplot2::geom_vline(mapping = aes(xintercept = 20), alpha = .5, linetype = "longdash") +
ggplot2::geom_vline(mapping = aes(xintercept = 40), alpha = .5, linetype = "longdash") +
ggplot2::scale_color_manual(values = df.primary_colors) +
ggplot2::scale_shape_manual(values = corsi_events) +
ggplot2::scale_fill_manual(values = df.primary_colors)
return(viz.corsi_graph)
}
#'Chart Corsi Events and Their Positions
#'
#'Create a visual representation of all corsi events for a given game and their position on the ice
#'
#'@param rawdata NHL RTSS data for a single game
#'@param color_list utilizes the hex colors stored in team_colors$primary unless otherwise specified
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_corsi_positions <- function(rawdata, color_list = team_colors) {
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
#Utilize enhanced_pbp to add more columns
df.enhanced_pbp <- enhanced_pbp(rawdata)
#Filter only corsi events
df.corsi_table <-
dplyr::filter(df.enhanced_pbp, event_type %in% names(corsi_events)) %>%
dplyr::group_by(event_team) %>%
dplyr::mutate(team_corsi = row_number())
#Add Corsi Points
chart.corsi_positions <-
rink +
ggplot2::labs(color = "Team", shape = "Shot Type") +
ggplot2::geom_point(data = filter(df.corsi_table, !is.na(side_coordsx) & !is.na(side_coordsy)),
mapping = aes(x = side_coordsx,
y = side_coordsy,
color = event_team,
shape = event_type),
size = 3) +
ggplot2::scale_color_manual(values = df.primary_colors) +
ggplot2::scale_shape_manual(values = corsi_events)
return(chart.corsi_positions)
}
#'Graphically Summarize Team Stats
#'
#'Create a graphical representation of specific team stats for a given game
#'
#'\itemize{
#' \item Blocks = Total blocks by each team
#' \item Hits = Total hits by each team
#' \item Faceoffs = Total faceoffs won by each team
#' \item Corsi = Total corsi events by each team
#' \item Shots = Total shots by each team
#' \item Goals = Total goals by each team
#'}
#'
#'@author Eric Fastner (eric.fastner@@gmail.com)
#'@export
viz_team_summary <- function(rawdata, color_list = team_colors) {
#DESCRIPTION - Use fun.team_summary to create a vizualization of team game performance
#Check if the rawdata only contains one game
if(length(unique(rawdata$game_id)) != 1){
print("Data can only contain one game per chart")
return(NULL)
}
#Set Home and Away Teams
home_team <- rawdata[[1,"home_team"]]
away_team <- rawdata[[1,"away_team"]]
#Grab Primary Colors
df.primary_colors <- as.character(color_list$Primary)
names(df.primary_colors) <- row.names(color_list)
df.team_summary <- get_team_stats(rawdata)
chart.team_summary <-
ggplot2::ggplot(data = df.team_summary, mapping = aes(x = factor(Event, levels = c("Blocks", "Hits", "Faceoffs", "Corsi", "Shots", "Goals")),
fill = factor(event_team, levels = c(as.character(away_team),as.character(home_team))),
y = Value)) +
ggplot2::ggtitle(paste("Team Summary")) +
ggplot2::labs(fill = "Team") +
ggplot2::theme(plot.title = element_text(hjust = 0.5),
panel.grid = element_blank(),
panel.background = element_blank(),
axis.ticks = element_blank(),
axis.text.y = element_text(size = 11, color = "black"),
axis.line.x = element_blank(),
axis.text.x = element_blank(),
axis.title = element_blank()) +
ggplot2::geom_col(position = "fill") +
ggplot2::geom_text(data = subset(df.team_summary, event_team == as.character(home_team)), position = position_fill(vjust = -0.025), mapping = aes(label = Value)) +
ggplot2::geom_text(data = subset(df.team_summary, event_team == as.character(away_team)), position = position_fill(vjust = 1.025), mapping = aes(label = Value)) +
ggplot2::geom_hline(yintercept = 0.5, linetype = "longdash", alpha = .75) +
ggplot2::coord_flip() +
ggplot2::scale_fill_manual(values = df.primary_colors)
return(chart.team_summary)
}
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