Heres a monte carlo simulator written in R. Personally I like tripling the bet each time, transferring out winnings once they reach a certain level then starting again. The thing with martingales is you are bound to lose eventually if you follow it strictly:
#install.packages("Rlab") # Run First Time
require(Rlab) #used for bernouilli distribution function rbern()
####Settings
#General
live.plot=F #Watch Simulation Live (runs slower)
max.bets<-1000 #Number of Bets to End Simulation
iterations<-1000 #Number of Simulations to Run
fee<-.0005 #Transaction Fee
#Bet Strategy and Satoshi Dice options
Win.Odds<-.5 #Odds of Winning
Price.Multiplier<-1.957 #Multiple of Bet Payed on Win
max.bet.size<-500 #Maximum Allowed Size of Bet
start.wallet<-10 #Starting Funds
lose.multiplier<-2 #Multiple of losing bet size to use for following bet
#End Settings
##Calulate Bet Sizes and Payouts
bet.num<-1:20
bet.size<-.01*lose.multiplier^(bet.num-1)
bet.size[which(bet.size>max.bet.size)]<-max.bet.size
win.size<-Price.Multiplier*.01*lose.multiplier^(bet.num-1)-fee
win.size[which(win.size>Price.Multiplier*max.bet.size)]<-Price.Multiplier*max.bet.size-fee
###Highest Density Interval Calculator Function (for the charts)
get.HDI<-function(sampleVec,credMass){
sortedPts = sort( sampleVec )
ciIdxInc = floor( credMass * length( sortedPts ) )
nCIs = length( sortedPts ) - ciIdxInc
ciWidth = rep( 0 , nCIs )
for ( i in 1:nCIs ) {
ciWidth[ i ] = sortedPts[ i + ciIdxInc ] - sortedPts[ i ]
}
HDImin = sortedPts[ which.min( ciWidth ) ]
HDImax = sortedPts[ which.min( ciWidth ) + ciIdxInc ]
HDIlim = c( HDImin , HDImax, credMass )
return( HDIlim )
}
####
######Run Simulation
if(live.plot==T){
dev.new()
}
out2=NULL
pb<-txtProgressBar(min = 0, max = iterations, initial = 0,style = 3)
for(j in 1:iterations){
wallet<-start.wallet
i<-1
t<-1
run.result=NULL
while(wallet>0 & t<=max.bets){
result<-rbern(1,Win.Odds)
if(result==0){
wallet<-wallet-bet.size[i]
color="Red"
i<-i+1
}
if(result==1){
wallet<-wallet-bet.size[i]+win.size[i]
color="Green"
i<-1
}
if(wallet>0){
t<-t+1
run.result<-rbind(run.result,cbind(j,t,wallet,i))
}
if(live.plot==T){
plot(run.result[,2],run.result[,3],
xlab="Bet Number", ylab="Coins in Wallet",
col=color,
main=paste("Simulation #",j)
)
}
}
out2<-rbind(out2,run.result)
setTxtProgressBar(pb, j)
}
close(pb)
#End Simulation
####Get Results
winning.iterations<-out2[which(out2[,2]==max.bets),1]
perc.wins<-100*length(which(out2[,2]==max.bets))/iterations
win.wallets<-out2[which(out2[,2]==max.bets),3]
hdi<-get.HDI(win.wallets,.95)
win.mode<-density(win.wallets)$x[
which(density(win.wallets)$y==
max(density(win.wallets)$y)
)]
fail.timepoints=matrix(nrow=(iterations-length(win.wallets)),ncol=1)
r<-1
for(i in 1:iterations){
temp<-out2[which(out2[,1]==i),]
if(max(temp[,2])<max.bets){
fail.timepoints[r]<-max(temp[,2])
r<-r+1
}
}
####Plot Results
dev.new()
layout(matrix(c(1,1,2,3),nrow=2,ncol=2,byrow=2))
#Plot Simulation Results
plot(0,0,type="n",
xlab="Bet Number", ylab="Coins in Wallet",
xlim=c(0,max(out2[,2])),ylim=c(0,max(out2[,3])),
main=c(paste("Starting Funds=", start.wallet, " Win Odds=", Win.Odds),
paste("Bet Multiplier After Loss= ",lose.multiplier,"x",sep=""),
paste("Maximum # of Bets=",max.bets, " # of Simulations=",iterations))
)
for(i in 1:iterations){
if(i %in% winning.iterations){
temp<-out2[which(out2[,1]==i),]
lines(temp[,2],temp[,3],col=rgb(0,1,0,.1))
}else{
temp<-out2[which(out2[,1]==i),]
lines(temp[,2],temp[,3],col=rgb(1,0,0,.1))
}
}
#Plot Distribution of non-zero Winnings
hist.counts<-hist(win.wallets, col="Green",
xlab="Final Wallet Amount",
breaks=seq(0,(max(win.wallets)+max(win.wallets)/10),by=max(win.wallets)/10),
main=c(paste("Percent of Winning Simulations=",perc.wins, "%"),
paste("Mode=",round(win.mode,2), " Mean=",round(mean(win.wallets),2))
),
sub=paste(round(100*hdi[3],3), "%", "HDI (Lower,Upper):",round(hdi[1],1),",",round(hdi[2],1))
)$count
rect(hdi[1],0,hdi[2],.025*max(hist.counts),col="Black")
#Plot Distribution of when Bankruptcy Occurred
hist(fail.timepoints, col="Red",
breaks=seq(0,(max(fail.timepoints)+max(fail.timepoints)/10),by=max(fail.timepoints)/10),
xlab="Bet Number at Bankruptcy",
main="Bet Number at Bankruptcy")
and mess with the settings at the top of the script you can simulate the outcomes of various strategies. It won't automate the betting for you though.
Edit: I can also modify it to match your specific strategy if you'd like.
