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Code for simulating the outcome of the Elam Ending
# Code for creating an Elam Ending simulation model #
rm(list = ls(all = TRUE))
library(dplyr)
library(tidyr)
loc<-"" # enter file path for exporting model output #
# point probabilities for each possession : 0-1-2-3-4 points #
tp<-c(0.505,0.031,0.325,0.137,0.002) # team with possession #
op<-c(0.505,0.031,0.325,0.137,0.002) # team without possession #
tpc<-cumsum(tp)
opc<-cumsum(op)
# simulate each ame state 10,000 times to create win probabilities #
# distance to target score: from 1 to 24 points #
# score differential: from -20 to +20 points #
gol<-vector('list')
mol<-vector('list')
for (str in 24:1) {
for (pos in 0:1) {
for (mgn in -20:20) {
print(paste(mgn,str,pos))
flush.console()
gs<-c(mgn,str,pos) # score margin, distance to target, possession #
gml<-vector('list')
edl<-vector('list')
for (j in 1:10000) {
m<-matrix(nrow=1001,ncol=7)
colnames(m)<-c("i","m","dst","pos","ts","os","s")
m[1,]<-c(0,gs,gs[1],0,NA)
for (i in 1:1000) {
g<-m[i,2:4]
if (g[3]==1) {p<-tpc} else {p<-opc}
r<-runif(n=1)
s<-findInterval(r,p)
m[i,7]<-s
g1<-ifelse(g[3]==1,g[1]+s,g[1]-s)
g2<-ifelse(g[3]==1,ifelse(g[1]<0,g[2]-max(0,s+g[1]),g[2]-s),ifelse(g[1]>0,g[2]-max(0,s-g[1]),g[2]-s))
g3<-ifelse(g[3]==1,0,1)
m[i+1,1]<-i
m[i+1,2]<-g1
m[i+1,3]<-g2
m[i+1,4]<-g3
m[i+1,5]<-ifelse(g[3]==1,m[i,5]+s,m[i,5])
m[i+1,6]<-ifelse(g[3]==0,m[i,6]+s,m[i,6])
if (g2<=0) {
m<-m[!is.na(m[,1]),]
break}
}
gml[[j]]<-m
edl[[j]]<-m[nrow(m),1:(ncol(m)-1)]
}
edd<-data.frame(do.call('rbind',edl),stringsAsFactors = F)
gmd<-data.frame(do.call('rbind',gml),stringsAsFactors = F)
gmd$cnt<-1
gma<-aggregate(gmd$cnt,by=list(gmd$m,gmd$dst),FUN=sum)
colnames(gma)<-c("m","dst","cnt")
gma<-cbind(mgn,str,pos,j,gma)
wp<-mean(edd$m>0)
mpos<-mean(edd$i)
mmgn<-mean(edd$m)
mmgnw<-mean(edd$m[edd$m>0])
mmgnl<-mean(edd$m[edd$m<0])
mgnz<-sum(edd$m==0)
mo<-matrix(nrow=1,ncol=10,data=c(mgn,str,pos,wp,mpos,mmgn,mmgnw,mmgnl,mgnz,j))
colnames(mo)<-c('mgn','str','pos','wp','mpos','mmgn','mmgnw','mmgnl','mgnz','j')
mol[[paste(mgn,str,pos)]]<-mo
gol[[paste(mgn,str,pos)]]<-gma
}
}
}
mod<-data.frame(do.call('rbind',mol),stringsAsFactors = F)
god<-data.frame(do.call('rbind',gol),stringsAsFactors = F)
out<-mod %>%
filter(mgn>=0, str>0) %>%
select(str,mgn,pos,wp,mpos,mmgn) %>%
arrange(-str,mgn,pos)
# raw data used for Elam Ending calculator #
write_csv(out,path=paste(loc,"elamcalc.csv"))
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