In TylerGrantSmith/pickem:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  root.dir = here::here()
)

library(pickem)
library(data.table)
input_file <- here::here("input","NFL Pool.xlsx")
results <- get_results(input_file, 1)
knitr::kable(results)

library(tidyverse)
library(data.table)
library(pickem)
input_file = here::here("input","NFL Pool.xlsx")
week = 1
probs = pickem::get_538_data()
pickem = pickem::read_pickem(input_file, week, probs)
outcomes = pickem:::generate_outcomes(probs, week)
points = pickem:::calculate_points(pickem, outcomes)
ranks = pickem:::calculate_ranks(points)

setDT(probs)
setDT(pickem)
setDT(outcomes)
setDT(points)
setDT(ranks)
name = "Jordan"
num_win_scenarios = ranks[RANK==1][NAME==name][,.N]

probs[outcomes[ranks[RANK==1][NAME==name], on = c("SIM_ID", "WEEK", "SCENARIO_PROB")], on = c("WEEK", "GAME_ID", "HOME_OR_AWAY" = "OUTCOME")][,.(.N,WIN_SCENARIO_PERCENT = scales::percent(.N/num_win_scenarios, 0.01)),TEAM][order(-N)]

probs[outcomes[ranks[RANK==1], on = c("SIM_ID", "WEEK", "SCENARIO_PROB"),allow.cartesian = TRUE], on = c("WEEK", "GAME_ID", "HOME_OR_AWAY" = "OUTCOME")][,.(.N,WIN_SCENARIO_PERCENT = scales::percent(.N/num_win_scenarios, 0.01)),TEAM][order(-N)]

x <-
  probs[outcomes[ranks[RANK==1], on = c("SIM_ID", "WEEK", "SCENARIO_PROB"), allow.cartesian = TRUE], on = c("WEEK", "GAME_ID", "HOME_OR_AWAY" = "OUTCOME")][,.(.N,WIN_SCENARIO_PERCENT = scales::percent(.N/num_win_scenarios, 0.01)),c('TEAM','NAME')] %>% dcast(TEAM ~ NAME, value.var = 'N')

y <-
  ranks[!is.na(NAME)][RANK == 1][,TIE_VALUE := 1/.N, SIM_ID] %>% 
  dcast(WEEK ~ NAME, value.var = 'RANK', fun.aggregate = sum)

y <- y[,-1]
x[,-1] / (replicate(32,y,simplify = T) %>% t %>% as.data.table() %>% mutate_all(as.double) %>% as.data.table())

bind_cols(x[,1],x[,-1] / (replicate(32,y,simplify = T) %>% t %>% as.data.table() %>% mutate_all(as.double) %>% as.data.table())) %>% mutate_all(replace_na, 0) %>% mutate_at(vars(-1), scales::percent,accuracy = 0.1)


out <-
  ranks[!is.na(NAME)][RANK == 1][,TIE_VALUE := 1/.N, SIM_ID][, VALUE:=1][,SCENARIO_PROB_TIE := SCENARIO_PROB * TIE_VALUE] %>% melt(measure.vars = c('VALUE','TIE_VALUE', 'SCENARIO_PROB', 'SCENARIO_PROB_TIE'), id.vars = c('NAME')) %>% dcast(variable ~ NAME, fun = sum)

out[,map(.SD, round, digits = 3), .SDcols = names(out)[-1]]

TylerGrantSmith/pickem documentation built on Sept. 28, 2019, 10:10 a.m.