Using Monte Carlo to find Best multiple

so we've shown some examples that look promising, but we're unsure about their variables, and we're not sure they wholistically beat doubler. Let's begin to work out that stuff. The question is, can we find a simple variable change where there is both lower risk, and higher profit... and soon, is this the case accross an average of 1 million samples.

import random
import matplotlib
import matplotlib.pyplot as plt
import time

lower_bust = 31.235
higher_profit = 63.208

# back to 1,000
sampleSize = 1000
startingFunds = 10000
wagerSize = 100
wagerCount = 100




def rollDice():
    roll = random.randint(1,100)

    if roll == 100:
        return False
    elif roll <= 50:
        return False
    elif 100 > roll >= 50:
        return True



def multiple_bettor(funds,initial_wager,wager_count):#,color):

    #add
    global multiple_busts
    global multiple_profits
    
    value = funds
    wager = initial_wager
    wX = []
    vY = []
    currentWager = 1
    previousWager = 'win'
    previousWagerAmount = initial_wager

    while currentWager <= wager_count:
        if previousWager == 'win':
            if rollDice():
                value += wager
                wX.append(currentWager)
                vY.append(value)
            else:
                value -= wager 
                previousWager = 'loss'
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)
                if value <= 0:
                    multiple_busts += 1
                    break
        elif previousWager == 'loss':
            if rollDice():

                #### must change the multiple ####
                wager = previousWagerAmount * random_multiple
                if (value - wager) <= 0:
                    wager = value
                    
                value += wager
                wager = initial_wager
                previousWager = 'win'
                wX.append(currentWager)
                vY.append(value)
            else:
                wager = previousWagerAmount * random_multiple
                if (value - wager) <= 0:
                    wager = value
                value -= wager
                previousWager = 'loss'
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)

                if value <= 0:
                    #change
                    multiple_busts += 1
                    break

        currentWager += 1

    #plt.plot(wX,vY)
    #####################
    if value > funds:
        #change
        multiple_profits+=1
    
    


def doubler_bettor(funds,initial_wager,wager_count,color):
    global doubler_busts
    global doubler_profits
    value = funds
    wager = initial_wager
    wX = []
    vY = []
    currentWager = 1
    previousWager = 'win'
    previousWagerAmount = initial_wager

    while currentWager <= wager_count:
        if previousWager == 'win':
            if rollDice():
                value += wager
                wX.append(currentWager)
                vY.append(value)
            else:
                value -= wager 
                previousWager = 'loss'
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)
                if value < 0:
                    currentWager += 10000000000000000
                    doubler_busts += 1
        elif previousWager == 'loss':
            if rollDice():
                wager = previousWagerAmount * 2
                if (value - wager) < 0:
                    wager = value
                    
                value += wager
                wager = initial_wager
                previousWager = 'win'
                wX.append(currentWager)
                vY.append(value)
            else:
                wager = previousWagerAmount * 2
                if (value - wager) < 0:
                    wager = value
                value -= wager
                previousWager = 'loss'
                previousWagerAmount = wager
                wX.append(currentWager)
                vY.append(value)

                if value <= 0:
                    currentWager += 10000000000000000
                    doubler_busts += 1

        currentWager += 1
    #plt.plot(wX,vY,color)
    #####################
    if value > funds:
        doubler_profits+=1

def simple_bettor(funds,initial_wager,wager_count,color):
    global simple_busts
    global simple_profits

    value = funds
    wager = initial_wager
    wX = []
    vY = []
    currentWager = 1
    while currentWager <= wager_count:
        if rollDice():
            value += wager
            wX.append(currentWager)
            vY.append(value)
        else:
            value -= wager
            wX.append(currentWager)
            vY.append(value)

            if value <= 0:
                currentWager += 10000000000000000
                simple_busts +=1
        currentWager += 1
    plt.plot(wX,vY,color)
    if value > funds:
        simple_profits+=1
x = 0

#Doubler Bettor Bust Chances: 84.1457... so anything less than this... aaaand
#Doubler Bettor Profit Chances: 15.6355 ... aaaand better than this.

while x < 10000:
    
    ######## move this stuff in here for the maths.
    multiple_busts = 0.0
    multiple_profits = 0.0
    # now we're wanting to do 100 attempts to get a good sample #
    multipleSampSize = 100000
    currentSample = 1
    
    random_multiple = random.uniform(0.1,10.0)
    #random_multiple = 2.00
    #print((random_multiple
    # adding this....
    while currentSample <= multipleSampSize:
        multiple_bettor(startingFunds,wagerSize,wagerCount)
        #add one to sample
        currentSample += 1

    if ((multiple_busts/multipleSampSize)*100.00 < lower_bust) and ((multiple_profits/multipleSampSize)*100.00 > higher_profit):
        print(('#################################################'))
        print(('found a winner, the multiple was:',random_multiple))
        print(('Lower Bust Rate Than:',lower_bust))
        print(('Higher profit rate than:',higher_profit))
        print(('Bust Rate:',(multiple_busts/multipleSampSize)*100.00))
        print(('Profit Rate:',(multiple_profits/multipleSampSize)*100.00))
        print(('#################################################'))
        time.sleep(5)
        #plt.show()
    else:
        pass
               

##        print(('####################################'))
##        print(('To beat:'))
##        print(('Lower Bust Rate Than:',lower_bust))
##        print(('Higher profit rate than:',higher_profit))
##        print(('Bust Rate:',(multiple_busts/multipleSampSize)*100.00))
##        print(('Profit Rate:',(multiple_profits/multipleSampSize)*100.00))
##        print(('####################################'))
##
##        #clears the figure
##        plt.clf()
        

    x+=1
		

The next tutorial: Checking betting results