[stealofhome]

I am still moving the top unsigned draftees into college. Here's the code for that. I imagine there's some kind of a loop that can combine the two and automatically create a table that will match up the draftees with a school.

#library(readr)
#library(dplyr)
#library(lubridate)
#teams <- read_csv("Out of the Park Developments/OOTP Baseball 19/saved_games/OOTPLeagueReborn.lg/import_export/general/teams.csv")
#leagues <- read_csv("Out of the Park Developments/OOTP Baseball 19/saved_games/OOTPLeagueReborn.lg/import_export/general/leagues.csv")

#import data (players_basic, players_value, players_career_pitching_stats, players_career_batting_stats)
players <- read_csv("Out of the Park Developments/OOTP Baseball 19/saved_games/OOTPLeagueReborn.lg/import_export/csv/players.csv")
players <- unite(players, name, c("first_name","last_name"), sep = " ")
players_value <- read_csv("Out of the Park Developments/OOTP Baseball 19/saved_games/OOTPLeagueReborn.lg/import_export/csv/players_value.csv")
ncaadate <- mdy(paste(3,"/",27,"/",as.numeric(players$age[players$player_id == '24']) + 
  as.numeric(year(players$date_of_birth[players$player_id == '24'])) + 1))

#Teams with fewer than 20 players
lowteams <- players %>% 
  filter(league_id == '208') %>% 
  group_by(team_id) %>% 
  tally() %>% 
  merge(teams[ , c("team_id", "name")], by = "team_id") %>% 
  arrange(n) %>% 
  filter(n < '20')

#Top unsigned players
draftees <- players %>%
  select(league_id, player_id, name, age, date_of_birth) %>% 
  merge(leagues[ , c("league_id", "league_level")], 
        by = "league_id", all = TRUE) %>% 
  merge(players_value[ , c("player_id", "offensive_value_talent", 
                           "pitching_value_talent")], 
        by = "player_id") %>% 
  replace_na(list(league_level = 0)) %>% 
  filter((league_id == '0' & age <= 19) | league_level == '11') %>% 
  mutate(nxtage = ncaadate - ymd(date_of_birth), 
         value = pmax(offensive_value_talent,pitching_value_talent)) %>% 
  filter(nxtage >= '6877' & value >=1000) %>% 
  arrange(desc(value)) %>%
  select(name)

View(lowteams)
View(draftees)