# simulating the winner of a game when the chance of them winning is given

I have this problem where there are two teams: a and b. They play a series of 5 games that are each independent of the other. The winner of each game is given a certain number of points. Whichever team has the most points at the end wins the series. Each game is played and there are no ties, either a or b wins. I am given the chances for each team to win for each game and the number of points each game is worth.

DATA

GAME A B PTS 1 33.5 65.8 1 2 76.2 23.0 2 3 46.8 53.2 3 4 12.2 75.4 4 5 65.3 8.40 5

I am trying to simulate a winner for each game, then based on who wins add up their scores for each game to give a winner of the series. This would be simulated for 100 5-game series. The part I am not sure about is how to simulate a winner for an individual game based on their chance of winning. I found this link on stat.exchange about simulating head to data. This post pointed to using BradleyTerry2 R package. I read through the article and example 3.3 looks similar to what I am trying to do though I am not really sure how to implement it or how it predicts a winner. If this is not the approach to take I am open for pointers.

Here is my code so far

    install.packages("BradleyTerry2")

a <- c(33.5,76.2,46.8,12.2,65.3)
b <- c(65.8,23,53.2,75.4,8.4)
pts <- c(1,2,3,4,5)

# simulate 100 5-game series
for (x in 1:100)
{
a_pts <- 0
b_pts <- 0

# loop through each game to predict winner
for (g in 1:5)
{
# predict winner of game
# this is where i need help

# give winning team pts
if(a[g]==1)
{
a_pts <- a_pts + pts[g]
}
if(b[g]==1)
{
b_pts <- b_pts + pts[g]
}
}

# tally up series won by a
if(a_pts > b_pts)
{
a_games[x] <- 1
}
if(a_pts < b_pts)
{
a_games[x] <- 0
}
}

# probability of a winning series
sum(a_games==1)/100


At this point I am just trying to figure out how to simulate the winner of an individual game based on their chance of winning. I will fix the checks to add points to the winner based on code/variables for predicting a winner. I am fairly new to both stats and R so any suggestions for generating a simulation either in R (preferable) or using statics equations I am open to hear.

• Are the probabilities of each team winning given in column A and column B? If so, and the columns represent percentages, shouldn't the sum of column A and column B for each game be 100 given there are no ties? – Wes Mar 25 '17 at 20:30
• Do these teams cross paths in game number 3? – Antoni Parellada Mar 25 '17 at 20:37
• @Wes yes columns a and b are the probabilities each team winning. I agree with you that they should equal a 100. Technically there was a third team which accounts for the missing percent, but through the course of the problem that was given me the third team was dropped and it was only looking at 2 teams. If it makes creating a simulation easier then the percent total for A and B can be made to equal a hundred. I am trying to understand how to do the simulation based on the probability of each team winning. – soccergal_66 Mar 25 '17 at 20:45
• @AntoniParellada A and B compete against each other in each game – soccergal_66 Mar 25 '17 at 20:46
• As perhaps an overly naive approach, you could use the rbinom() function and the probability of success for a given team? This would give you a vector indicating successes and losses for that given game... and should be OK given each game is independent. Something along the lines of a<-rbinom(100,1,0.335) for game 1, with values of 1 indicating a win for team A. Just focusing on that as you say that is the part you are having difficulties with – Wes Mar 25 '17 at 20:55

Here is the code solution I came up with based on @Wes suggestion of using rbinom. I modified and cleaned up my code. This will loop through each game using rbinom to generate a 0 or 1 for N number of simulations using the probability P of winning the game. It will then loop through each game and assign the corresponding points for the games in the 5 game series if the value is 1

    a <- c(33.5,76.2,46.8,12.2,65.3)
b <- c(65.8,23,53.2,75.4,8.4)
pts <- c(1,2,3,4,5)
N <- 100
a_pts <- rep(0,N)

# loop through each game to predict winner
for (g in 1:5)
{
# predict winner of game
P <- a[g]/100
a_games <- rbinom(N,1,P)

# loop through each game and assign corresponding points
for (x in 1:N)
{
if(a_games[x]==1)
{
a_pts[x] <- a_pts[x] + pts[g]
}
}
}

# probability of a winning series
sum(a_pts>=8)/N

• A word of caution, using the values a as the probability for the rbinom() function does not correspond to the probabilities defined in b (see my comment on sum of probabilities above). Defining b and b_pts is essentially redundant in this code. – Wes Mar 25 '17 at 23:26
• @Wes I agree. thanks. I removed the line. I thought I had removed all the references to b when I had cleaned up the code. – soccergal_66 Mar 26 '17 at 0:12

I don't know R but i would solve the problem like this :

While (!stop) { If (Rnd ()<=a [g]/100) a wins stop=true; If (Rnd ()<=b [g]/100) b wins stop=true; }

Rnd () is the random generator giving a real number between 0 and 1

However i don't understand your check for winner :

If (a [g]==1)

You should use another variable to store who won a particular game if you want to reuse the lists a [] and b []

• I don't think this answer is very helpful. I think the problem is with the lack of clarity if the question. – Michael Chernick Mar 25 '17 at 20:30