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Shiny_All_Functions.R
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#####################################################################################
##### SHINY All Functions || 05/22/2019 #####
#####################################################################################
## major notes and additions
## thanks to the work of those before who did much of the important stuff here:
## Manny, The Evolving Wild Team, etc
## major changes are mostly that the xg metrics are bunk here, intentionally, for design reasons
## stylistically need to add dplyr:: before select if you've got MASS installed
library(xgboost)
# Basic Functions
standardize <- function(metric) {
x <- (metric - mean(na.omit(metric))) / sd(na.omit(metric))
}
peek <- function(object, number) {
head(colnames(object), number)
}
## ------------------------------------------------------ ##
## ------------ ##
## xG Model ##
## ------------ ##
##################
fun.pbp_expand <- function(data) {
data$event_description <- as.character(data$event_description)
data$coords_x <- as.numeric(as.character(data$coords_x))
data$coords_y <- as.numeric(as.character(data$coords_y))
print("expand", quote = F)
hold <- data %>%
# Manny's enhanced pbp functions
mutate(event_circle =
1 * (coords_x <= -25 & coords_y > 0) +
2 * (coords_x <= -25 & coords_y < 0) +
3 * (coords_x < 0 & coords_x > 25 & coords_y > 0) +
4 * (coords_x < 0 & coords_x > 25 & coords_y < 0) +
5 * (abs(coords_x) < 5 & abs(coords_y) < 5) +
6 * (coords_x > 0 & coords_x < 25 & coords_y > 0) +
7 * (coords_x > 0 & coords_x < 25 & coords_y < 0) +
8 * (coords_x >= 25 & coords_y > 0) +
9 * (coords_x >= 25 & coords_y < 0),
event_rinkside = ifelse(coords_x <= -25, "L",
ifelse(coords_x > -25 & coords_x < 25, "N",
ifelse(coords_x >= 25, "R", NA))),
event_zone = ifelse((grepl("off. zone", tolower(event_description)) == TRUE), "Off",
ifelse((grepl("neu. zone", tolower(event_description)) == TRUE), "Neu",
ifelse((grepl("def. zone", tolower(event_description)) == TRUE), "Def", NA))),
event_zone = ifelse(event_zone == "Def" & event_type == "BLOCK", "Off", event_zone),
home_zone = ifelse(event_team == away_team & event_zone == "Off", "Def",
ifelse(event_team == away_team & event_zone == "Def", "Off", event_zone)),
# Initial distance / angle calculation
pbp_distance = suppressWarnings(as.numeric(sub(".*Zone, *(.*?) * ft.*", "\\1", event_description))),
pbp_distance = ifelse(event_type %in% st.fenwick_events & is.na(pbp_distance), 0, pbp_distance),
event_distance = sqrt((89 - abs(coords_x))^2 + coords_y^2),
event_angle = abs(atan(coords_y / (89 - abs(coords_x))) * (180 / pi)),
# Update distance calc for long shots (and various mistakes)
event_distance = ifelse(event_type %in% st.fenwick_events & pbp_distance > 89 & coords_x < 0 &
event_detail != "Tip-In" & event_detail != "Wrap-around" & event_detail != "Deflected" & !(pbp_distance > 89 & event_zone == "Off"),
sqrt((abs(coords_x) + 89)^2 + coords_y^2),
ifelse(event_type %in% st.fenwick_events & pbp_distance > 89 & coords_x > 0 &
event_detail != "Tip-In" & event_detail != "Wrap-around" & event_detail != "Deflected" & !(pbp_distance > 89 & event_zone == "Off"),
sqrt((coords_x + 89)^2 + coords_y^2),
event_distance)),
event_angle = ifelse(event_type %in% st.fenwick_events & pbp_distance > 89 & coords_x < 0 &
event_detail != "Tip-In" & event_detail != "Wrap-around" & event_detail != "Deflected" & !(pbp_distance > 89 & event_zone == "Off"),
abs( atan(coords_y / (abs(coords_x) + 89)) * (180 / pi)),
ifelse(event_type %in% st.fenwick_events & pbp_distance > 89 & coords_x > 0 &
event_detail != "Tip-In" & event_detail != "Wrap-around" & event_detail != "Deflected" & !(pbp_distance > 89 & event_zone == "Off"),
abs(atan(coords_y / (coords_x + 89)) * (180 / pi)),
event_angle)),
event_zone = ifelse(event_type %in% st.fenwick_events & event_zone == "Def" & pbp_distance <= 64, "Off", event_zone),
# Update penalty shot strength states
game_strength_state = ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == home_team, "Ev1",
ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == away_team, "1vE", game_strength_state)),
home_skaters = ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == home_team, 1,
ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == away_team, 0, home_skaters)),
away_skaters = ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == home_team, 0,
ifelse((grepl("penalty shot", tolower(event_description)) == TRUE) & event_team == away_team, 1, away_skaters))
)
)
print("face_ID", quote = F)
# Add home_zonestart for corsi events
face_index <- hold %>%
filter(event_type %in% c(st.corsi_events, "FAC"),
game_period < 5
) %>%
) %>%
arrange(game_id, event_index) %>%
mutate(face_index = cumsum(event_type == "FAC")) %>%
group_by(game_id, face_index) %>%
arrange(event_index) %>%
mutate(test = first(home_zone),
home_zonestart = ifelse(first(home_zone) == "Def", 1,
ifelse(first(home_zone) == "Neu", 2,
ifelse(first(home_zone) == "Off", 3, NA)))
) %>%
ungroup() %>%
dplyr::select(game_id, event_index, home_zonestart) %>%
) %>%
ungroup() %>%
dplyr::select(game_id, event_index, home_zonestart) %>%
data.frame()
# Join
print("join", quote = F)
print("---", quote = F)
hold <- left_join(hold, face_index, by = c("game_id", "event_index"))
}
}
fun.pbp_index <- function(data) {
# Add shift/face/pen indexes & shift IDs
print("index", quote = F)
pbp_hold <- data %>%
arrange(game_id, event_index) %>%
mutate(face_index = cumsum(event_type == "FAC"),
shift_index = cumsum(event_type == "ON"),
pen_index = cumsum(event_type == "PENL"))
print("shift_ID", quote = F)
hold <- pbp_hold %>%
filter(event_type %in% c("FAC", "GOAL", "BLOCK", "SHOT", "MISS", "HIT", "TAKE", "GIVE"),
game_period < 5
) %>%
) %>%
group_by(game_id, game_period, season,
home_on_1, home_on_2, home_on_3, home_on_4, home_on_5, home_on_6,
away_on_1, away_on_2, away_on_3, away_on_4, away_on_5, away_on_6,
home_goalie, away_goalie,
face_index, shift_index, pen_index
) %>%
) %>%
mutate(shift_ID = round(first(event_index) * as.numeric(game_id))) %>%
summarise(shift_ID = first(shift_ID),
shift_length = last(game_seconds) - first(game_seconds)) %>%
ungroup() %>%
dplyr::select(game_id, game_period, season, shift_ID, face_index,
shift_index, pen_index, shift_length, home_on_1:away_goalie
) %>%
dplyr::select(game_id, game_period, season, shift_ID, face_index,
shift_index, pen_index, shift_length, home_on_1:away_goalie
) %>%
data.frame()
print("join", quote = F)
print("---", quote = F)
join <- left_join(pbp_hold, hold, by = c("game_id", "game_period", "season",
"home_on_1", "home_on_2", "home_on_3",
"home_on_4", "home_on_5", "home_on_6",
"away_on_1", "away_on_2", "away_on_3",
"away_on_4","away_on_5", "away_on_6",
"home_goalie", "away_goalie",
"face_index", "shift_index", "pen_index"))
}
}
fun.pbp_prep <- function(data, prep_type) {
# Prep pbp for xG models (EV or UE)
if (prep_type == "EV") {
# Prep for EV xG model
pbp_prep_EV <- data %>%
filter(event_type %in% c("FAC", "GOAL", "BLOCK", "SHOT", "MISS", "HIT", "TAKE", "GIVE"),
game_period < 5,
!(grepl("penalty shot", tolower(event_description))),
!is.na(coords_x),
!is.na(coords_y),
!(coords_x == 0 & coords_y == 0 & event_type %in% st.corsi_events &
(pbp_distance != 90 & event_type %in% st.fenwick_events))
) %>%
) %>%
group_by(season, game_id, game_period) %>%
arrange(event_index) %>%
mutate(seconds_since_last = game_seconds - lag(game_seconds),
event_type_last = lag(event_type),
event_team_last = lag(event_team),
event_strength_last = lag(game_strength_state),
coords_x_last = lag(coords_x),
coords_y_last = lag(coords_y)
) %>%
) %>%
ungroup() %>%
arrange(season, game_id, event_index) %>%
filter(event_type %in% st.fenwick_events,
game_strength_state %in% st.even_strength,
!is.na(coords_x_last),
!is.na(coords_y_last)
) %>%
) %>%
# Create priors
mutate(same_team_last = 1 * (event_team == event_team_last),
is_home = 1 * (event_team == home_team),
score_state = ifelse(is_home == 1, home_score - away_score, away_score - home_score),
event_detail = ifelse(is.na(event_detail), "Wrist", event_detail),
distance_from_last = sqrt((coords_x - coords_x_last)^2 + (coords_y - coords_y_last)^2),
# Flurry indicator
flurry = 1 * (shift_ID == lag(shift_ID, default = 0) & event_team == lag(event_team)),
# Probably a better way to do this...
flurry_1 = ifelse(flurry == 1 & lag(flurry) == 1, 2, flurry),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 2, 3, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 3, 4, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 4, 5, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 5, 6, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 6, 7, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 7, 8, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 8, 9, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 9, 10, flurry_1)
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
game_strength_state, game_score_state, score_state, is_home,
event_player_1, home_goalie, away_goalie,
home_score, away_score, home_team, away_team, home_skaters, away_skaters,
event_description, event_team, event_type, event_detail,
coords_x, coords_y, pbp_distance, shot_distance, shot_angle,
event_team_last, same_team_last, event_strength_last, event_type_last,
seconds_since_last, distance_from_last, coords_x_last, coords_y_last,
shift_ID, shift_length, flurry
) %>%
data.frame()
}
) %>%
data.frame()
}
else if (prep_type == "UE") {
# Prep for UE xG model
pbp_prep_UE <- data %>%
filter(event_type %in% c("FAC", "GOAL", "BLOCK", "SHOT", "MISS", "HIT", "TAKE", "GIVE"),
game_period < 5,
!(grepl("penalty shot", tolower(event_description))),
!is.na(coords_x),
!is.na(coords_y),
!(coords_x == 0 & coords_y == 0 & event_type %in% st.corsi_events &
(pbp_distance != 90 & event_type %in% st.fenwick_events))
) %>%
) %>%
group_by(season, game_id, game_period) %>%
arrange(event_index) %>%
mutate(seconds_since_last = game_seconds - lag(game_seconds),
event_type_last = lag(event_type),
event_team_last = lag(event_team),
event_strength_last = lag(game_strength_state),
coords_x_last = lag(coords_x),
coords_y_last = lag(coords_y),
true_strength_state = paste0(home_skaters, "v", away_skaters)
) %>%
group_by(season, game_id, pen_index) %>%
mutate(pen_seconds_since = (game_strength_state %in% st.pp_strength) * (game_seconds - first(game_seconds)),
pen_seconds_since = ifelse(pen_seconds_since > 0 & pen_seconds_since >= 300, 120, pen_seconds_since)
) %>%
) %>%
group_by(season, game_id, pen_index) %>%
mutate(pen_seconds_since = (game_strength_state %in% st.pp_strength) * (game_seconds - first(game_seconds)),
pen_seconds_since = ifelse(pen_seconds_since > 0 & pen_seconds_since >= 300, 120, pen_seconds_since)
) %>%
ungroup() %>%
arrange(season, game_id, event_index) %>%
filter(event_type %in% st.fenwick_events,
(event_team == home_team & (game_strength_state %in% c("5v4", "5v3", "4v3") | true_strength_state %in% c("6v5", "6v4"))) |
(event_team == away_team & (game_strength_state %in% c("4v5", "3v5", "3v4") | true_strength_state %in% c("5v6", "4v6"))),
!is.na(coords_x_last),
!is.na(coords_y_last)
) %>%
) %>%
# Create priors
mutate(same_team_last = 1 * (event_team == event_team_last),
is_home = 1 * (event_team == home_team),
score_state = ifelse(is_home == 1, home_score - away_score, away_score - home_score),
event_detail = ifelse(is.na(event_detail), "Wrist", event_detail),
distance_from_last = sqrt((coords_x - coords_x_last)^2 + (coords_y - coords_y_last)^2),
prior_event_EV = 1 * (event_strength_last %in% st.even_strength),
# Flurry indicator
flurry = 1 * (shift_ID == lag(shift_ID, default = 0) & event_team == lag(event_team)),
# Probably a better way to do this...
flurry_1 = ifelse(flurry == 1 & lag(flurry) == 1, 2, flurry),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 2, 3, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 3, 4, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 4, 5, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 5, 6, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 6, 7, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 7, 8, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 8, 9, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 9, 10, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 10, 11, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 11, 12, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 12, 13, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 13, 14, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 14, 15, flurry_1)
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
game_strength_state, true_strength_state, game_score_state, score_state, is_home,
event_player_1, home_goalie, away_goalie,
home_score, away_score, home_team, away_team, home_skaters, away_skaters,
event_description, event_team, event_type, event_detail,
coords_x, coords_y, pbp_distance, shot_distance, shot_angle,
event_team_last, same_team_last, event_strength_last, prior_event_EV, event_type_last,
seconds_since_last, pen_seconds_since, distance_from_last, coords_x_last, coords_y_last,
shift_ID, shift_length, flurry
) %>%
data.frame()
}
) %>%
data.frame()
}
else if (prep_type == "SH") {
# Prep for SH xG model
pbp_prep_SH <- data %>%
filter(event_type %in% c("FAC", "GOAL", "BLOCK", "SHOT", "MISS", "HIT", "TAKE", "GIVE"),
game_period < 5,
!(grepl("penalty shot", tolower(event_description))),
!is.na(coords_x),
!is.na(coords_y),
!(coords_x == 0 & coords_y == 0 & event_type %in% st.corsi_events &
(pbp_distance != 90 & event_type %in% st.fenwick_events))
) %>%
) %>%
group_by(season, game_id, game_period) %>%
arrange(event_index) %>%
mutate(seconds_since_last = game_seconds - lag(game_seconds),
event_type_last = lag(event_type),
event_team_last = lag(event_team),
event_strength_last = lag(game_strength_state),
coords_x_last = lag(coords_x),
coords_y_last = lag(coords_y),
shift_ID = as.numeric(shift_ID)
) %>%
group_by(season, game_id, pen_index) %>%
mutate(pen_seconds_since = (game_strength_state %in% st.pp_strength) * (game_seconds - first(game_seconds)),
pen_seconds_since = ifelse(pen_seconds_since > 0 & pen_seconds_since >= 300, 120, pen_seconds_since)
) %>%
) %>%
group_by(season, game_id, pen_index) %>%
mutate(pen_seconds_since = (game_strength_state %in% st.pp_strength) * (game_seconds - first(game_seconds)),
pen_seconds_since = ifelse(pen_seconds_since > 0 & pen_seconds_since >= 300, 120, pen_seconds_since)
) %>%
ungroup() %>%
arrange(season, game_id, event_index) %>%
filter(event_type %in% st.fenwick_events,
event_team == away_team & game_strength_state %in% c("5v4", "5v3", "4v3") |
event_team == home_team & game_strength_state %in% c("4v5", "3v5", "3v4"),
!is.na(coords_x_last),
!is.na(coords_y_last)
) %>%
) %>%
mutate(same_team_last = 1 * (event_team == event_team_last),
is_home = 1 * (event_team == home_team),
score_state = ifelse(is_home == 1, home_score - away_score, away_score - home_score),
event_detail = ifelse(is.na(event_detail), "Wrist", event_detail),
distance_from_last = sqrt((coords_x - coords_x_last)^2 + (coords_y - coords_y_last)^2),
prior_event_EV = 1 * (event_strength_last %in% st.even_strength),
# Flurry indicator
flurry = 1 * (shift_ID == lag(shift_ID, default = 0) & event_team == lag(event_team)),
# Probably a better way to do this...
flurry_1 = ifelse(flurry == 1 & lag(flurry) == 1, 2, flurry),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 2, 3, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 3, 4, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 4, 5, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 5, 6, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 6, 7, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 7, 8, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 8, 9, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 9, 10, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 10, 11, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 11, 12, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 12, 13, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 13, 14, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 14, 15, flurry_1)
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
game_strength_state, game_score_state, score_state, is_home,
event_player_1, home_goalie, away_goalie,
home_score, away_score, home_team, away_team, home_skaters, away_skaters,
event_description, event_team, event_type, event_detail,
coords_x, coords_y, pbp_distance, shot_distance, shot_angle,
event_team_last, same_team_last, event_strength_last, prior_event_EV, event_type_last,
seconds_since_last, pen_seconds_since, distance_from_last, coords_x_last, coords_y_last,
shift_ID, shift_length, flurry
) %>%
data.frame()
}
) %>%
data.frame()
}
else if (prep_type == "EN") {
# Prep for EN xG model
pbp_prep_EN <- data %>%
filter(event_type %in% c("FAC", "GOAL", "BLOCK", "SHOT", "MISS", "HIT", "TAKE", "GIVE"),
game_period < 5,
!(grepl("penalty shot", tolower(event_description))),
!is.na(coords_x),
!is.na(coords_y),
!(coords_x == 0 & coords_y == 0 & event_type %in% st.corsi_events &
(pbp_distance != 90 & event_type %in% st.fenwick_events))
) %>%
) %>%
group_by(season, game_id, game_period) %>%
arrange(event_index) %>%
mutate(seconds_since_last = game_seconds - lag(game_seconds),
event_type_last = lag(event_type),
event_team_last = lag(event_team),
event_strength_last = lag(game_strength_state),
coords_x_last = lag(coords_x),
coords_y_last = lag(coords_y),
shift_ID = as.numeric(shift_ID)
) %>%
) %>%
group_by(season, game_id, pen_index) %>%
ungroup() %>%
arrange(season, game_id, event_index) %>%
filter(event_type %in% st.fenwick_events,
(event_team == away_team & game_strength_state %in% c("Ev5", "Ev4", "Ev3") & (home_skaters == 6 | away_skaters == 6)) |
(event_team == home_team & game_strength_state %in% c("5vE", "4vE", "3vE") & (home_skaters == 6 | away_skaters == 6)),
!is.na(coords_x_last),
!is.na(coords_y_last)
) %>%
) %>%
mutate(same_team_last = 1 * (event_team == event_team_last),
is_home = 1 * (event_team == home_team),
score_state = ifelse(is_home == 1, home_score - away_score, away_score - home_score),
event_detail = ifelse(is.na(event_detail), "Wrist", event_detail),
distance_from_last = sqrt((coords_x - coords_x_last)^2 + (coords_y - coords_y_last)^2),
# Flurry indicator
flurry = 1 * (shift_ID == lag(shift_ID, default = 0) & event_team == lag(event_team)),
# Probably a better way to do this...
flurry_1 = ifelse(flurry == 1 & lag(flurry) == 1, 2, flurry),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 2, 3, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 3, 4, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 4, 5, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 5, 6, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 6, 7, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 7, 8, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 8, 9, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 9, 10, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 10, 11, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 11, 12, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 12, 13, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 13, 14, flurry_1),
flurry_1 = ifelse(flurry == 1 & lag(flurry_1) == 14, 15, flurry_1)
) %>%
dplr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
) %>%
dplyr::select(-c(flurry)) %>%
rename(shot_distance = event_distance,
shot_angle = event_angle,
flurry = flurry_1
) %>%
dplyr::select(game_id, event_index, season, game_date, game_period, game_seconds,
game_strength_state, game_score_state, score_state, is_home,
event_player_1, home_goalie, away_goalie,
home_score, away_score, home_team, away_team, home_skaters, away_skaters,
event_description, event_team, event_type, event_detail,
coords_x, coords_y, pbp_distance, shot_distance, shot_angle,
event_team_last, same_team_last, event_strength_last, event_type_last,
seconds_since_last, distance_from_last, coords_x_last, coords_y_last,
shift_ID, shift_length, flurry
) %>%
filter(!is.na(shot_distance),
!is.na(shot_angle)
) %>%
data.frame()
}
}
) %>%
filter(!is.na(shot_distance),
!is.na(shot_angle)
) %>%
data.frame()
}
}
fun.model_prep <- function(data, prep_type) {
# Prep model data frames (EV or UE)
if (prep_type == "EV") {
# Create EV dummy variables, returns a matrix.
model_prep <- data %>%
mutate(is_goal = 1 * (event_type == "GOAL"),
state_5v5 = 1 * (game_strength_state == "5v5"),
state_4v4 = 1 * (game_strength_state == "4v4"),
state_3v3 = 1 * (game_strength_state == "3v3"),
score_down_4 = 1 * (score_state <= -4),
score_down_3 = 1 * (score_state == -3),
score_down_2 = 1 * (score_state == -2),
score_down_1 = 1 * (score_state == -1),
score_even = 1 * (score_state == 0),
score_up_1 = 1 * (score_state == 1),
score_up_2 = 1 * (score_state == 2),
score_up_3 = 1 * (score_state == 3),
score_up_4 = 1 * (score_state >= 4),
wrist_shot = 1 * (event_detail == "Wrist"),
deflected_shot = 1 * (event_detail == "Deflected"),
tip_shot = 1 * (event_detail == "Tip-In"),
slap_shot = 1 * (event_detail == "Slap"),
backhand_shot = 1 * (event_detail == "Backhand"),
snap_shot = 1 * (event_detail == "Snap"),
wrap_shot = 1 * (event_detail == "Wrap-around"),
prior_shot_same = 1 * (event_type_last == "SHOT" & same_team_last == 1),
prior_miss_same = 1 * (event_type_last == "MISS" & same_team_last == 1),
prior_block_same = 1 * (event_type_last == "BLOCK" & same_team_last == 1),
prior_shot_opp = 1 * (event_type_last == "SHOT" & same_team_last == 0),
prior_miss_opp = 1 * (event_type_last == "MISS" & same_team_last == 0),
prior_block_opp = 1 * (event_type_last == "BLOCK" & same_team_last == 0),
prior_give_opp = 1 * (event_type_last == "GIVE" & same_team_last == 0),
prior_give_same = 1 * (event_type_last == "GIVE" & same_team_last == 1),
prior_take_opp = 1 * (event_type_last == "TAKE" & same_team_last == 0),
prior_take_same = 1 * (event_type_last == "TAKE" & same_team_last == 1),
prior_hit_opp = 1 * (event_type_last == "HIT" & same_team_last == 0),
prior_hit_same = 1 * (event_type_last == "HIT" & same_team_last == 1),
prior_face = 1 * (event_type_last == "FAC")
) %>%
dplyr::select(is_goal,
) %>%
dplyr::select(is_goal,
shot_distance, shot_angle, is_home,
state_5v5:state_3v3,
score_down_4:score_up_4,
game_seconds, game_period, coords_x, coords_y, coords_x_last, coords_y_last,
wrist_shot:wrap_shot, distance_from_last, seconds_since_last,
prior_shot_same:prior_face) %>%
data.matrix()
}
}
else if (prep_type == "UE") {
# Create UE dummy variables, returns a matrix.
model_prep <- data %>%
mutate(is_goal = 1 * (event_type == "GOAL"),
state_5v4 = 1 * ((true_strength_state == "5v4" & event_team == home_team) | (true_strength_state == "4v5" & event_team == away_team)),
state_5v3 = 1 * ((true_strength_state == "5v3" & event_team == home_team) | (true_strength_state == "3v5" & event_team == away_team)),
state_4v3 = 1 * ((true_strength_state == "4v3" & event_team == home_team) | (true_strength_state == "3v4" & event_team == away_team)),
state_6v5 = 1 * ((true_strength_state == "6v5" & event_team == home_team) | (true_strength_state == "5v6" & event_team == away_team)),
state_6v4 = 1 * ((true_strength_state == "6v4" & event_team == home_team) | (true_strength_state == "4v6" & event_team == away_team)),
score_down_4 = 1 * (score_state <= -4),
score_down_3 = 1 * (score_state == -3),
score_down_2 = 1 * (score_state == -2),
score_down_1 = 1 * (score_state == -1),
score_even = 1 * (score_state == 0),
score_up_1 = 1 * (score_state == 1),
score_up_2 = 1 * (score_state == 2),
score_up_3 = 1 * (score_state == 3),
score_up_4 = 1 * (score_state >= 4),
wrist_shot = 1 * (event_detail == "Wrist"),
deflected_shot = 1 * (event_detail == "Deflected"),
tip_shot = 1 * (event_detail == "Tip-In"),
slap_shot = 1 * (event_detail == "Slap"),
backhand_shot = 1 * (event_detail == "Backhand"),
snap_shot = 1 * (event_detail == "Snap"),
wrap_shot = 1 * (event_detail == "Wrap-around"),
prior_shot_same = 1 * (event_type_last == "SHOT" & same_team_last == 1),
prior_miss_same = 1 * (event_type_last == "MISS" & same_team_last == 1),
prior_block_same = 1 * (event_type_last == "BLOCK" & same_team_last == 1),
prior_shot_opp = 1 * (event_type_last == "SHOT" & same_team_last == 0),
prior_miss_opp = 1 * (event_type_last == "MISS" & same_team_last == 0),
prior_block_opp = 1 * (event_type_last == "BLOCK" & same_team_last == 0),
prior_give_same = 1 * (event_type_last == "GIVE" & same_team_last == 1),
prior_take_same = 1 * (event_type_last == "TAKE" & same_team_last == 1),
prior_hit_same = 1 * (event_type_last == "HIT" & same_team_last == 1),
prior_give_opp = 1 * (event_type_last == "GIVE" & same_team_last == 0),
prior_take_opp = 1 * (event_type_last == "TAKE" & same_team_last == 0),
prior_hit_opp = 1 * (event_type_last == "HIT" & same_team_last == 0),
prior_face = 1 * (event_type_last == "FAC")
) %>%
dplyr::select(is_goal,
) %>%
dplyr::select(is_goal,
shot_distance, shot_angle, is_home,
state_5v4:state_6v4,
score_down_4:score_up_4,
game_seconds, game_period, coords_x, coords_y, coords_x_last, coords_y_last,
wrist_shot:wrap_shot, distance_from_last, seconds_since_last, prior_event_EV,
pen_seconds_since, prior_shot_same:prior_face
) %>%
data.matrix()
}
) %>%
data.matrix()
}
else if (prep_type == "SH") {
# Create SH dummy variables, returns a matrix.
model_prep_SH <- data %>%
mutate(is_goal = 1 * (event_type == "GOAL"),
state_4v5 = 1 * ((game_strength_state == "5v4" & event_team == away_team) | (game_strength_state == "4v5" & event_team == home_team)),
state_3v5 = 1 * ((game_strength_state == "5v3" & event_team == away_team) | (game_strength_state == "3v5" & event_team == home_team)),
state_3v4 = 1 * ((game_strength_state == "4v3" & event_team == away_team) | (game_strength_state == "3v4" & event_team == home_team)),
score_down_4 = 1 * (score_state <= -4),
score_down_3 = 1 * (score_state == -3),
score_down_2 = 1 * (score_state == -2),
score_down_1 = 1 * (score_state == -1),
score_even = 1 * (score_state == 0),
score_up_1 = 1 * (score_state == 1),
score_up_2 = 1 * (score_state == 2),
score_up_3 = 1 * (score_state == 3),
score_up_4 = 1 * (score_state >= 4),
wrist_shot = 1 * (event_detail == "Wrist"),
deflected_shot = 1 * (event_detail == "Deflected"),
tip_shot = 1 * (event_detail == "Tip-In"),
slap_shot = 1 * (event_detail == "Slap"),
backhand_shot = 1 * (event_detail == "Backhand"),
snap_shot = 1 * (event_detail == "Snap"),
wrap_shot = 1 * (event_detail == "Wrap-around"),
prior_shot_same = 1 * (event_type_last == "SHOT" & same_team_last == 1),
prior_miss_same = 1 * (event_type_last == "MISS" & same_team_last == 1),
prior_block_same = 1 * (event_type_last == "BLOCK" & same_team_last == 1),
prior_shot_opp = 1 * (event_type_last == "SHOT" & same_team_last == 0),
prior_miss_opp = 1 * (event_type_last == "MISS" & same_team_last == 0),
prior_block_opp = 1 * (event_type_last == "BLOCK" & same_team_last == 0),
prior_give_same = 1 * (event_type_last == "GIVE" & same_team_last == 1),
prior_take_same = 1 * (event_type_last == "TAKE" & same_team_last == 1),
prior_hit_same = 1 * (event_type_last == "HIT" & same_team_last == 1),
prior_give_opp = 1 * (event_type_last == "GIVE" & same_team_last == 0),
prior_take_opp = 1 * (event_type_last == "TAKE" & same_team_last == 0),
prior_hit_opp = 1 * (event_type_last == "HIT" & same_team_last == 0),
prior_face = 1 * (event_type_last == "FAC")
) %>%
dplyr::select(is_goal,
) %>%
dplyr::select(is_goal,
shot_distance, shot_angle, is_home,
state_4v5:state_3v4,
score_down_4:score_up_4,
game_seconds, game_period, coords_x, coords_y, coords_x_last, coords_y_last,
wrist_shot:wrap_shot, distance_from_last, seconds_since_last, prior_event_EV,
pen_seconds_since, prior_shot_same:prior_face) %>%
data.matrix()
}
}
else if (prep_type == "EN") {
# Create EN dummy variables, returns a matrix.
model_prep_EN <- data %>%
mutate(is_goal = 1 * (event_type == "GOAL"),
state_Ev5 = 1 * ((game_strength_state == "Ev5" & event_team == away_team) | (game_strength_state == "5vE" & event_team == home_team)),
state_Ev4 = 1 * ((game_strength_state == "Ev4" & event_team == away_team) | (game_strength_state == "4vE" & event_team == home_team)),
state_Ev3 = 1 * ((game_strength_state == "Ev3" & event_team == away_team) | (game_strength_state == "3vE" & event_team == home_team)),
score_down_4 = 1 * (score_state <= -4),
score_down_3 = 1 * (score_state == -3),
score_down_2 = 1 * (score_state == -2),
score_down_1 = 1 * (score_state == -1),
score_even = 1 * (score_state == 0),
score_up_1 = 1 * (score_state == 1),
score_up_2 = 1 * (score_state == 2),
score_up_3 = 1 * (score_state == 3),
score_up_4 = 1 * (score_state >= 4),
wrist_shot = 1 * (event_detail == "Wrist"),
deflected_shot = 1 * (event_detail == "Deflected"),
tip_shot = 1 * (event_detail == "Tip-In"),
slap_shot = 1 * (event_detail == "Slap"),
backhand_shot = 1 * (event_detail == "Backhand"),
snap_shot = 1 * (event_detail == "Snap"),
wrap_shot = 1 * (event_detail == "Wrap-around"),
prior_shot_same = 1 * (event_type_last == "SHOT" & same_team_last == 1),
prior_miss_same = 1 * (event_type_last == "MISS" & same_team_last == 1),
prior_block_same = 1 * (event_type_last == "BLOCK" & same_team_last == 1),
prior_shot_opp = 1 * (event_type_last == "SHOT" & same_team_last == 0),
prior_miss_opp = 1 * (event_type_last == "MISS" & same_team_last == 0),
prior_block_opp = 1 * (event_type_last == "BLOCK" & same_team_last == 0),
prior_give_same = 1 * (event_type_last == "GIVE" & same_team_last == 1),
prior_take_same = 1 * (event_type_last == "TAKE" & same_team_last == 1),
prior_hit_same = 1 * (event_type_last == "HIT" & same_team_last == 1),
prior_give_opp = 1 * (event_type_last == "GIVE" & same_team_last == 0),
prior_take_opp = 1 * (event_type_last == "TAKE" & same_team_last == 0),
prior_hit_opp = 1 * (event_type_last == "HIT" & same_team_last == 0),
prior_face = 1 * (event_type_last == "FAC")
) %>%
dplyr::select(is_goal,
) %>%
dplyr::select(is_goal,
shot_distance, shot_angle, is_home,
state_Ev5:state_Ev3,
score_down_4:score_up_4,
game_seconds, game_period, coords_x, coords_y, coords_x_last, coords_y_last,
wrist_shot:wrap_shot, distance_from_last, seconds_since_last,
prior_shot_same:prior_face) %>%
data.matrix()
}
}
}
}
### added by mhbw to make model_EV, model_UE, model_SH, model_EN functional
## first create the data matrix
## for this pull in the data as pulled down in the script 'EH_scrape_functions.R'
## and renamed as pbp_base_new
## other important note: this is no way intended as a valid usable model, nor should it be read to truly
## replicate the work of the folks at evolving wild; it's a place holder to make the scrape function
## essentially; ignore it and don't use features derived from it for any other model building or conclusions
# Convert for use with XGBoost and predict goal probability
## ----------------- ##
## Even-Strength ##
## ----------------- ##
# Full run
fun.pbp_full_add <- function(data, model_EV, model_UE, model_SH, model_EN) {
### Function should be run using unprocessed scraped pbp data. Returns a list of 5 data frames:
## ~$pbp_full - full pbp data with extras and xG probabilities for both EV and UE situations
## ~$pbp_prep_EV - EV prep data frame for xG model evaluation
## ~$pbp_prep_UE - UE prep data frame for xG model evaluation
## ~$pbp_prep_SH - SH prep data frame for xG model evaluation
## ~$pbp_prep_EN - EN prep data frame for xG model evaluation
# Initial prep of scraped pbp data.
pbp_part <- fun.pbp_expand(data)
pbp_part <- fun.pbp_index(pbp_part)
# Convert for use with XGBoost and predict goal probability
## ----------------- ##
## Even-Strength ##
## ----------------- ##
print("predict_EV", quote = F)
pbp_prep_EV <- fun.pbp_prep(pbp_part, "EV")
model_prep_EV <- fun.model_prep(pbp_prep_EV, "EV")
model_prep_EV <- Matrix(model_prep_EV, sparse = TRUE)
pred_matrix_EV <- model_prep_EV[, 2:ncol(model_prep_EV)]
xgb_matrix_EV <- xgb.DMatrix(data = pred_matrix_EV)
pbp_prep_EV$pred_XGB_7 <- predict(object = model_EV, xgb_matrix_EV)
pred_goal_EV <- dplyr::select(pbp_prep_EV, game_id, event_index, pred_XGB_7)
is_goal_vect <- model_prep_EV[, 1]
pred_matrix_EV <- model_prep_EV[, 2:ncol(model_prep_EV)]
xgb_matrix_EV <- xgb.DMatrix(data = pred_matrix_EV,label=is_goal_vect)
param_7_EV <- list(objective = "binary:logistic",
eval_metric = "logloss",
eval_metric = "auc",
eta = .068,
gamma = .12,
subsample = .78,
max.depth = 6,
colsample_bytree = .76,
min_child_weight = 5,
max_delta_step = 5,
nthread = 4)
model_EV = xgb.train(data = xgb_matrix_EV,
params = param_7_EV, # Determined and set above
nround = 189,
verbose = 2
)
pbp_prep_EV$pred_XGB_7 <- predict(object = model_EV, xgb_matrix_EV)
pred_goal_EV <- dplyr::select(pbp_prep_EV, game_id, event_index, pred_XGB_7)
## ------------------- ##
## Uneven-Strength ##
## ------------------- ##
print("predict_UE", quote = F)