Run this code, making sure all the packages are installed (install.packages("package")
if you don't).
Make sure to replace the instances of FILENAME where you want to save your data.
library(tidyverse)
library(dplyr)
library(na.tools)
first <- 2009 #first season to grab. min available=2009
last <- 2018 # most recent season
datalist = list()
for (yr in first:last) {
pbp <- read_csv(url(paste0("https://github.com/ryurko/nflscrapR-data/raw/master/play_by_play_data/regular_season/reg_pbp_", yr, ".csv")))
games <- read_csv(url(paste0("https://raw.githubusercontent.com/ryurko/nflscrapR-data/master/games_data/regular_season/reg_games_", yr, ".csv")))
pbp <- pbp %>% inner_join(games %>% distinct(game_id, week, season)) %>% select(-fumble_recovery_2_yards)
datalist[[yr]] <- pbp # add it to your list
}
pbp_all <- dplyr::bind_rows(datalist)
pbp_all %>% group_by(home_team) %>%summarize(n=n(), seasons=n_distinct(season), minyr=min(season), maxyr=max(season)) %>%
arrange(seasons)
pbp_all <- pbp_all %>%
mutate_at(vars(home_team, away_team, posteam, defteam), funs(case_when(
. %in% "JAX" ~ "JAC",
. %in% "STL" ~ "LA",
. %in% "SD" ~ "LAC",
TRUE ~ .
)))
#save the whole big thing in case you need it later
saveRDS(pbp_all, file="FILENAME_ALL.rds")
pbp_all <- readRDS("FILENAME_ALL.rds")
pbp_all_rp <- pbp_all %>%
filter(!is_na(epa), !is_na(posteam), play_type=="no_play" | play_type=="pass" | play_type=="run") %>%
mutate(
pass = if_else(str_detect(desc, "( pass)|(sacked)|(scramble)"), 1, 0),
rush = if_else(str_detect(desc, "(left end)|(left tackle)|(left guard)|(up the middle)|(right guard)|(right tackle)|(right end)") & pass == 0, 1, 0),
success = ifelse(epa>0, 1 , 0),
passer_player_name = ifelse(play_type == "no_play" & pass == 1,
str_extract(desc, "(?<=\\s)[A-Z][a-z]*\\.\\s?[A-Z][A-z]+(\\s(I{2,3})|(IV))?(?=\\s((pass)|(sack)|(scramble)))"),
passer_player_name),
receiver_player_name = ifelse(play_type == "no_play" & str_detect(desc, "pass"),
str_extract(desc,
"(?<=to\\s)[A-Z][a-z]*\\.\\s?[A-Z][A-z]+(\\s(I{2,3})|(IV))?"),
receiver_player_name),
rusher_player_name = ifelse(play_type == "no_play" & rush == 1,
str_extract(desc, "(?<=\\s)[A-Z][a-z]*\\.\\s?[A-Z][A-z]+(\\s(I{2,3})|(IV))?(?=\\s((left end)|(left tackle)|(left guard)|(up the middle)|(right guard)|(right tackle)|(right end)))"),
rusher_player_name),
name = ifelse(!is_na(passer_player_name), passer_player_name, rusher_player_name),
yards_gained=ifelse(play_type=="no_play",NA,yards_gained),
play=1
) %>%
filter(pass==1 | rush==1)
saveRDS(pbp_all_rp, file="FILENAME_RP.rds") #save
pbp_all_rp<- readRDS("FILENAME_RP.rds") #how to load it later
#roster data
datalist = list()
for (yr in first:last) {
if (yr<=2017) {
roster <- read_csv(url(paste0("https://raw.githubusercontent.com/ryurko/nflscrapR-data/master/legacy_data/team_rosters/team_", yr, "_rosters.csv")))
roster <- roster %>% mutate(
season = Season,
full_player_name = Player,
abbr_player_name = name,
position = Pos,
team = Team,
gsis_id = GSIS_ID
) %>%
select(season,full_player_name,abbr_player_name,position,team,gsis_id)
}
else {
roster <- read_csv(url(paste0("https://raw.githubusercontent.com/ryurko/nflscrapR-data/master/roster_data/regular_season/reg_roster_", yr, ".csv")))
roster <- roster %>% select(-season_type)
}
datalist[[yr]] <- roster # add it to your list
}
rosters_all <- dplyr::bind_rows(datalist)
#fix the team name problems
rosters_all <- rosters_all %>%
mutate_at(vars(team), funs(case_when(
. %in% "JAX" ~ "JAC",
. %in% "STL" ~ "LA",
. %in% "SD" ~ "LAC",
TRUE ~ .
)))
#save raw dataset
saveRDS(rosters_all, file="FILENAME.rds")
Add that to the select line. Change:
pbp <- pbp %>% inner_join(games %>% distinct(game_id, week, season)) %>% select(-fumble_recovery_2_yards)
To
pbp <- pbp %>% inner_join(games %>% distinct(game_id, week, season)) %>% select(-fumble_recovery_2_yards, -blocked_player_id)
Plays that are all
NA
in some seasons but not others cause issues, so dropping it fixes it.