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PlayerEval.R
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PlayerEval.R
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## Player eval stats ##
## xTadded for each player on passes and cumulative xT added for each
## player.
## Calculate these as totals and as per event. Again do when under pressure and when not under pressure
## Maybe split the field in thirds, xT added in each third when facing pressure and when not facing pressure.
## Rank players based on xT added under pressure, 1-10 based on percentiles
## Want cumulative xT added including turnovers+shots, just passes/dribbles, just pass/dribbles with no turnovers
## repeat with under pressure
## Then get all these statistics per event
## 12 total metrics
check_majority <- function(vector_positions){
return(names(sort(table(vector_positions),decreasing=TRUE)[1]))
}
check_position <- function(position){
if(str_detect(toString(position), "Back")) {return("Back")}
else if (str_detect(toString(position), "Midfield")) {return("Midfield")}
else {return("Forward")}
}
# Cumulative xT added
library(tidyverse)
statsbomb_events <- read.csv("Statsbombevents_xTadded.csv", row.names = 1)
statsbomb_events <- statsbomb_events %>% group_by(player.id) %>% filter(n() > 300)
xT_cumulative <- statsbomb_events %>% group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
total_xT = sum(xT_added)) %>%
arrange(desc(total_xT))
statsbomb_passes_dribbles <- statsbomb_events %>% filter(type.id %in% c(30, 14))
xT_passes_dribbles <- statsbomb_passes_dribbles %>% group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
total_xT = sum(xT_added)) %>%
arrange(desc(total_xT))
xT_passes_dribbles_noturnovers <- statsbomb_passes_dribbles %>% filter(is.na(pass.outcome.id) | dribble.outcome.id==8) %>%
group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
total_xT = sum(xT_added)) %>%
arrange(desc(total_xT))
total_xT_pressure <- statsbomb_events %>% group_by(player.id) %>% filter(!is.na(under_pressure)) %>%
summarise(
total_xT_pressure = sum(xT_added)) %>%
arrange(desc(total_xT_pressure))
xT_cumulative <- xT_cumulative %>% inner_join(total_xT_pressure)
rm(total_xT_pressure)
xT_passes_dribbles_pressure <- statsbomb_passes_dribbles %>% group_by(player.id) %>%
filter(!is.na(under_pressure)) %>%
summarise(
total_xT_pressure = sum(xT_added)) %>%
arrange(desc(total_xT_pressure))
xT_passes_dribbles <- xT_passes_dribbles %>% inner_join(xT_passes_dribbles_pressure)
rm(xT_passes_dribbles_pressure)
xT_passes_dribbles_noturnovers_pressure <- statsbomb_passes_dribbles %>% filter(is.na(pass.outcome.id) | dribble.outcome.id==8) %>%
filter(!is.na(under_pressure)) %>%
group_by(player.id) %>%
summarise(
total_xT_pressure = sum(xT_added)) %>%
arrange(desc(total_xT_pressure))
xT_passes_dribbles_noturnovers <- xT_passes_dribbles_noturnovers %>%
inner_join(xT_passes_dribbles_noturnovers_pressure)
rm(xT_passes_dribbles_noturnovers_pressure)
## Now repeat per event ##
xT_perevent <- statsbomb_events %>% group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
xT_per_event = sum(xT_added)/n()) %>%
arrange(desc(xT_per_event))
xT_passes_dribbles_perevent <- statsbomb_passes_dribbles %>% group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
xT_per_event = sum(xT_added)/n()) %>%
arrange(desc(xT_per_event))
xT_passes_dribbles_noturnovers_perevent <- statsbomb_passes_dribbles %>% filter(is.na(pass.outcome.id) | dribble.outcome.id==8) %>%
group_by(player.id) %>%
summarise(
name = unique(player.name),
position = check_position(check_majority(position.name)),
team = check_majority(team.name),
xT_per_event = sum(xT_added)/n()) %>%
arrange(desc(xT_per_event))
xT_pressure_perevent <- statsbomb_events %>% group_by(player.id) %>% filter(!is.na(under_pressure)) %>%
summarise(
xT_pressure_perevent = sum(xT_added)/n()) %>%
arrange(desc(xT_pressure_perevent))
xT_perevent <- xT_perevent %>% inner_join(xT_pressure_perevent)
rm(xT_pressure_perevent)
xT_passes_dribbles_pressure_perevent <- statsbomb_passes_dribbles %>% group_by(player.id) %>%
filter(!is.na(under_pressure)) %>%
summarise(
xT_pressure_perevent = sum(xT_added)/n()) %>%
arrange(desc(xT_pressure_perevent))
xT_passes_dribbles_perevent <- xT_passes_dribbles_perevent %>% inner_join(xT_passes_dribbles_pressure_perevent)
rm(xT_passes_dribbles_pressure_perevent)
xT_passes_dribbles_noturnovers_pressure_perevent <- statsbomb_passes_dribbles %>% filter(is.na(pass.outcome.id) | dribble.outcome.id==8) %>%
filter(!is.na(under_pressure)) %>%
group_by(player.id) %>%
summarise(
xT_pressure_perevent = sum(xT_added)/n()) %>%
arrange(desc(xT_pressure_perevent))
xT_passes_dribbles_noturnovers_perevent <- xT_passes_dribbles_noturnovers_perevent %>%
inner_join(xT_passes_dribbles_noturnovers_pressure_perevent)
rm(xT_passes_dribbles_noturnovers_pressure_perevent)
quantile(xT_passes_dribbles_noturnovers_perevent$xT_pressure_perevent, seq(0,1,0.1))
xT_passes_dribbles_noturnovers_perevent[xT_passes_dribbles_noturnovers_perevent$team=="Arsenal WFC",]
quantile(rev(xT_perevent$xT_per_event - xT_perevent$xT_pressure_perevent), seq(0,1,0.1))
xT_perevent$resiliency <- xT_perevent$xT_per_event-xT_perevent$xT_pressure_perevent
xT_perevent[xT_perevent$team=="Arsenal WFC",]