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code-for-viz.R
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code-for-viz.R
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library(StatsBombR)
library(dplyr)
##################################################################################################
# Function to plot For a Specific Team
##################################################################################################
statsbomb_flank_attack = function(matchData,team_name,sub_title){
require(dplyr)
require(ggplot2)
`%notin%` = Negate(`%in%`)
# Selecting all attempted carries, passes and excluding injury-clearance-passes (fairplay).
matchData = dplyr::filter(matchData,type.name %in% c("Carry","Pass") & type.id %notin% c(74))
data <- NULL
for (i in c(1:(nrow(matchData)))) {
if(matchData$type.name[i]=="Carry")
{
start_x = sapply(matchData$location[i],function(x) x[][1])
start_y = sapply(matchData$location[i],function(x) x[][2])
end_x = sapply(matchData$carry.end_location[i],function(x) x[][1])
end_y = sapply(matchData$carry.end_location[i],function(x) x[][2])
outcome = "Complete"
team = matchData$possession_team.name[i]
data = rbind(data,data.frame(team,type="Carry",start_x,start_y,outcome,end_x,end_y))
}
else if(matchData$type.name[i]=="Pass")
{
start_x = sapply(matchData$location[i],function(x) x[][1])
start_y = sapply(matchData$location[i],function(x) x[][2])
end_x = sapply(matchData$pass.end_location[i],function(x) x[][1])
end_y = sapply(matchData$pass.end_location[i],function(x) x[][2])
outcome = ifelse(is.na(matchData$pass.outcome.name[i])==TRUE,"Complete",matchData$pass.outcome.name[i])
team = matchData$possession_team.name[i]
data = rbind(data,data.frame(team,type="Pass",start_x,start_y,outcome,end_x,end_y))
}
}
# labelling origin zones
data$origin[(data$start_x<79.2 & (data$start_y<=26.4))]="left"
data$origin[(data$start_x<79.2 & (data$start_y>26.4 & data$start_y<=52.8))]="center"
data$origin[(data$start_x<79.2 & (data$start_y>52.8))]="right"
data$origin = as.factor(data$origin)
# labelling final third zones
data$entry[(data$end_x>=79.2 & (data$end_y<=26.4))]="left"
data$entry[(data$end_x>=79.2 & (data$end_y>26.4 & data$end_y<=52.8))]="center"
data$entry[(data$end_x>=79.2 & (data$end_y>52.8))]="right"
data$entry = as.factor(data$entry)
data = dplyr::filter(data,outcome %notin% c("Injury Clearance") )
data$origin <- factor(data$origin, levels = c("left", "center", "right"))
data$entry <- factor(data$entry, levels = c("left", "center", "right"))
# finding attempted entries into the final 3rd.
temp = filter(data,team == team_name) %>% na.omit(cols= entry,origin)
att = temp %>% select(entry) %>% table()
att_entry_depth = mutate(temp,`entry_depth`=
round(sqrt(((79.2-end_x)/120*105)**2+((start_y-end_y)/80*68)**2),1)) %>%
select(entry,entry_depth) %>%
group_by(entry) %>%
summarise("att_entry_depth" = round(mean(entry_depth),0)) %>%
as.data.frame() %>% select(att_entry_depth) %>% t()
att_distribution_pct = round(att/sum(att)*100,1) %>% round(0)
# finding successful entries into the final 3rd.
temp = filter(data,team == team_name & outcome=="Complete") %>% na.omit(cols= entry,origin)
suc = temp %>% select(entry) %>% table()
suc_entry_depth = mutate(temp,`entry_depth`=
round(sqrt(((79.2-end_x)/120*105)**2+((start_y-end_y)/80*68)**2),1)) %>%
select(entry,entry_depth) %>%
group_by(entry) %>%
summarise("suc_entry_depth" = round(mean(entry_depth),0)) %>%
as.data.frame() %>% select(suc_entry_depth) %>% t()
suc_pct = round(suc/(att)*100,1) %>% round(0)
data = rbind(att,att_distribution_pct,att_entry_depth,suc,suc_pct,suc_entry_depth) %>%
as.data.frame()
# Plotting the flank attacks viz.
pitch_line_color = "black"
title_color = "black"
viz_color = "black"
ggplot() +
labs(title = paste(team_name,"- Entries into Final 3rd"),
subtitle = sub_title)+
coord_flip() +
geom_rect(aes(xmin = 100, xmax = 100.2, ymin = 44.2, ymax = 55.8), fill = pitch_line_color, colour =pitch_line_color , size = 0.5) +
geom_rect(aes(xmin = 50, xmax = 100, ymin = 0, ymax = 100), fill = NA, colour = pitch_line_color, size = 0.5) +
geom_rect(aes(xmin = 83, xmax = 100, ymin = 21, ymax = 79), fill = NA, colour = pitch_line_color, size = 0.5) +
geom_rect(aes(xmin = 100, xmax = 94, ymin = 36.8, ymax = 63.2), fill = NA, colour = pitch_line_color, size = 0.5) +
#geom_point(aes(x=50,y=50), colour = viz_color,lwd=2) +geom_point(aes(x=88.5,y=50), colour = viz_color,lwd=2)+
# right D box arc
#geom_curve(aes(x = 83, y = 40, xend = 83, yend = 60, colour = "curve"), colour = viz_color, size = 0.5,ncp = 1000)+
# centre Kickoff circle
#geom_curve(aes(x = 50, y = 36.8, xend = 50, yend = 63.2, colour = "curve"),curvature = 1,colour = viz_color, size = 0.5,ncp = 1000)+
#geom_curve(aes(x = 50, y = 63.2, xend = 50, yend = 36.8, colour = "curve"),curvature = 1, colour = viz_color, size = 0.5,ncp = 1000)+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "#f9f9fa"),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
plot.background = element_rect(fill = "#f9f9fa"),
plot.title = element_text(colour = title_color,
size = 26, face ="bold", hjust = 0.5),
plot.subtitle = element_text(colour = title_color,
size = 12, hjust = 0.5),
axis.title.x = element_blank(),
legend.position = "none",
legend.background = element_blank(),
legend.text = element_blank(),
legend.key = element_blank(),
legend.title = element_blank(),
text=element_text(size=16)) +
geom_segment(aes(x=60,
xend=66.7+data$left[3]-5,
y=20,
yend=20),
size=10,color = alpha(viz_color,data$left[5]/100))+
geom_segment(aes(x=60,
xend=66.7+data$center[3]-5,
y=50,
yend=50),
size=10, color = alpha(viz_color,data$center[5]/100))+
geom_segment(aes(x=60,
xend=66.7+data$right[3]-5,
y=80,
yend=80),
size=10, color = alpha(viz_color,data$right[5]/100))+
geom_polygon(aes(c(66.7+data$left[3]-5,66.7+data$left[3],66.7+data$left[3]-5), c(15,20,25)),
fill = alpha(viz_color,data$left[5]/100))+
geom_polygon(aes(c(66.7+data$center[3]-5,66.7+data$center[3],66.7+data$center[3]-5), c(45,50,55)),
fill = alpha(viz_color,data$center[5]/100))+
geom_polygon(aes(c(66.7+data$right[3]-5,66.7+data$right[3],66.7+data$right[3]-5), c(75,80,85)),
fill = alpha(viz_color,data$right[5]/100))+
geom_text(aes(55,20,label = paste(data$left[2],"%",sep = "")),color=viz_color,size=10) +
geom_text(aes(55,50,label = paste(data$center[2],"%",sep = "")),color=viz_color,size=10) +
geom_text(aes(55,80,label = paste(data$right[2],"%",sep = "")),color=viz_color,size=10)+
annotation_custom(grid::rasterGrob(png::readPNG("./statsbomb.png")
, interpolate = TRUE)
, xmin = 45, xmax = 50, ymin = 80, ymax = 100)+
geom_text(aes(48,10,label = paste("@npranav10")),color=viz_color,size=6)+
geom_text(aes(103,15,label = paste("Height: Avg Depth (Attempts)")),color=viz_color,size=4)+
geom_text(aes(103,50,label = paste("Color Scale: Success % ")),color=viz_color,size=4)+
geom_text(aes(103,85,label = paste("Number(%): Distribution (Attempts)")),color=viz_color,size=4)
return(data)
}
##################################################################################################
# Function to plot For a Specific Player
##################################################################################################
statsbomb_flank_attack_player = function(matchData,player_name,sub_title){
require(dplyr)
require(ggplot2)
`%notin%` <- Negate(`%in%`)
# Selecting all attempted carries, passes and excluding injury-clearance-passes (fairplay).
matchData = dplyr::filter(matchData,type.name %in% c("Carry","Pass") & type.id %notin% c(74))
data <- NULL
for (i in c(1:(nrow(matchData)))) {
if(matchData$type.name[i]=="Carry")
{
start_x = sapply(matchData$location[i],function(x) x[][1])
start_y = sapply(matchData$location[i],function(x) x[][2])
end_x = sapply(matchData$carry.end_location[i],function(x) x[][1])
end_y = sapply(matchData$carry.end_location[i],function(x) x[][2])
outcome = "Complete"
player = matchData$player.name[i]
data = rbind(data,data.frame(player,type="Carry",start_x,start_y,outcome,end_x,end_y))
}
else if(matchData$type.name[i]=="Pass")
{
start_x = sapply(matchData$location[i],function(x) x[][1])
start_y = sapply(matchData$location[i],function(x) x[][2])
end_x = sapply(matchData$pass.end_location[i],function(x) x[][1])
end_y = sapply(matchData$pass.end_location[i],function(x) x[][2])
outcome = ifelse(is.na(matchData$pass.outcome.name[i])==TRUE,"Complete",matchData$pass.outcome.name[i])
player = matchData$player.name[i]
data = rbind(data,data.frame(player,type="Pass",start_x,start_y,outcome,end_x,end_y))
}
}
# labelling origin zones
data$origin[(data$start_x<79.2 & (data$start_y<=26.4))]="left"
data$origin[(data$start_x<79.2 & (data$start_y>26.4 & data$start_y<=52.8))]="center"
data$origin[(data$start_x<79.2 & (data$start_y>52.8))]="right"
data$origin = as.factor(data$origin)
# labelling final third zones
data$entry[(data$end_x>=79.2 & (data$end_y<=26.4))]="left"
data$entry[(data$end_x>=79.2 & (data$end_y>26.4 & data$end_y<=52.8))]="center"
data$entry[(data$end_x>=79.2 & (data$end_y>52.8))]="right"
data$entry = as.factor(data$entry)
data = dplyr::filter(data,outcome %notin% c("Injury Clearance") )
data$origin <- factor(data$origin, levels = c("left", "center", "right"))
data$entry <- factor(data$entry, levels = c("left", "center", "right"))
# finding attempted entries into the final 3rd.
temp = filter(data,player == player_name) %>% na.omit(cols= entry,origin)
att = temp %>% select(entry) %>% table()
att_entry_depth = mutate(temp,`entry_depth`=
round(sqrt(((79.2-end_x)/120*105)**2+((start_y-end_y)/80*68)**2),1)) %>%
select(entry,entry_depth) %>%
group_by(entry) %>%
summarise("att_entry_depth" = round(mean(entry_depth),0)) %>%
as.data.frame() %>% select(att_entry_depth) %>% t()
att_distribution_pct = round(att/sum(att)*100,1) %>% round(0)
# finding successful entries into the final 3rd.
temp = filter(data,player == player_name & outcome=="Complete") %>% na.omit(cols= entry,origin)
suc = temp %>% select(entry) %>% table()
suc_entry_depth = mutate(temp,`entry_depth`=
round(sqrt(((79.2-end_x)/120*105)**2+((start_y-end_y)/80*68)**2),1)) %>%
select(entry,entry_depth) %>%
group_by(entry) %>%
summarise("suc_entry_depth" = round(mean(entry_depth),0)) %>%
as.data.frame() %>% select(suc_entry_depth) %>% t()
suc_pct = round(suc/(att)*100,1) %>% round(0)
data = rbind(att,att_distribution_pct,att_entry_depth,suc,suc_pct,suc_entry_depth) %>%
as.data.frame()
# Plotting the flank attacks viz.
pitch_line_color = "black"
title_color = "black"
viz_color = "black"
ggplot() +
labs(title = paste(player_name,"- Entries into Final 3rd"),
subtitle = sub_title)+
coord_flip() +
geom_rect(aes(xmin = 100, xmax = 100.2, ymin = 44.2, ymax = 55.8), fill = pitch_line_color, colour =pitch_line_color , size = 0.5) +
geom_rect(aes(xmin = 50, xmax = 100, ymin = 0, ymax = 100), fill = NA, colour = pitch_line_color, size = 0.5) +
geom_rect(aes(xmin = 83, xmax = 100, ymin = 21, ymax = 79), fill = NA, colour = pitch_line_color, size = 0.5) +
geom_rect(aes(xmin = 100, xmax = 94, ymin = 36.8, ymax = 63.2), fill = NA, colour = pitch_line_color, size = 0.5) +
#geom_point(aes(x=50,y=50), colour = viz_color,lwd=2) +geom_point(aes(x=88.5,y=50), colour = viz_color,lwd=2)+
# right D box arc
#geom_curve(aes(x = 83, y = 40, xend = 83, yend = 60, colour = "curve"), colour = viz_color, size = 0.5,ncp = 1000)+
# centre Kickoff circle
#geom_curve(aes(x = 50, y = 36.8, xend = 50, yend = 63.2, colour = "curve"),curvature = 1,colour = viz_color, size = 0.5,ncp = 1000)+
#geom_curve(aes(x = 50, y = 63.2, xend = 50, yend = 36.8, colour = "curve"),curvature = 1, colour = viz_color, size = 0.5,ncp = 1000)+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = "#f9f9fa"),
axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
plot.background = element_rect(fill = "#f9f9fa"),
plot.title = element_text(colour = title_color,
size = 26, face ="bold", hjust = 0.5),
plot.subtitle = element_text(colour = title_color,
size = 12, hjust = 0.5),
axis.title.x = element_blank(),
legend.position = "none",
legend.background = element_blank(),
legend.text = element_blank(),
legend.key = element_blank(),
legend.title = element_blank(),
text=element_text(size=16)) +
geom_segment(aes(x=60,
xend=66.7+data$left[3]-5,
y=20,
yend=20),
size=10,color = alpha(viz_color,data$left[5]/100))+
geom_segment(aes(x=60,
xend=66.7+data$center[3]-5,
y=50,
yend=50),
size=10, color = alpha(viz_color,data$center[5]/100))+
geom_segment(aes(x=60,
xend=66.7+data$right[3]-5,
y=80,
yend=80),
size=10, color = alpha(viz_color,data$right[5]/100))+
geom_polygon(aes(c(66.7+data$left[3]-5,66.7+data$left[3],66.7+data$left[3]-5), c(15,20,25)),
fill = alpha(viz_color,data$left[5]/100))+
geom_polygon(aes(c(66.7+data$center[3]-5,66.7+data$center[3],66.7+data$center[3]-5), c(45,50,55)),
fill = alpha(viz_color,data$center[5]/100))+
geom_polygon(aes(c(66.7+data$right[3]-5,66.7+data$right[3],66.7+data$right[3]-5), c(75,80,85)),
fill = alpha(viz_color,data$right[5]/100))+
geom_text(aes(55,20,label = paste(data$left[2],"%",sep = "")),color=viz_color,size=10) +
geom_text(aes(55,50,label = paste(data$center[2],"%",sep = "")),color=viz_color,size=10) +
geom_text(aes(55,80,label = paste(data$right[2],"%",sep = "")),color=viz_color,size=10)+
annotation_custom(grid::rasterGrob(png::readPNG("./statsbomb.png")
, interpolate = TRUE)
, xmin = 45, xmax = 50, ymin = 80, ymax = 100)+
geom_text(aes(48,10,label = paste("@npranav10")),color=viz_color,size=6)+
geom_text(aes(103,15,label = paste("Height: Avg Depth (Attempts)")),color=viz_color,size=4)+
geom_text(aes(103,50,label = paste("Color Scale: Success % ")),color=viz_color,size=4)+
geom_text(aes(103,85,label = paste("Number(%): Distribution (Attempts)")),color=viz_color,size=4)
return(data)
}