That’s a Bingo!

Creating the math model for a player vs. player Bingo game is easy. What is left of the pot when the commission has been deducted is distributed e.g. according to an hour-glass shape over the winning tickets, perhaps something like the table below.


Or maybe more of a funnel-shape.


Mission accomplished?

Well, in most cases not. We may want to add a jackpot which is paid out should a ticket obtain 1 row Bingo within, say, 13 drawn numbers. Or give out free tickets for the next round when the marked numbers on a ticket form a certain pattern. In order to control and fine-tune the playing experience, such as hit rates and average amounts paid for these bonus features, we need to know the probabilities for the respective events to occur.

For simplicity, let’s consider a Mini-Bingo, where each ticket consists of a 3×3 square grid of (nine) numbers between 1 and 21 inclusively. We want to calculate the probability of filling one row within k called numbers, where k ranges from 0 to 21. It does not matter which one of the three horizontal rows we fill, any of them will do.

Obviously, for k<3 the probability is 0 and for k>18 the probability is 1. For general k, we may perform the calculations in two steps, step A and step B.

A. Given that k numbers have been called, where k=0,1,…,21, find the probability that exactly j of them are present on the ticket.

B. Given that exactly j numbers have been marked on the ticket, find the probability that at least one row has been filled. Here, j ranges between 0 and 9.

We can then combine the two steps to find the probability that at least one row has been filled after k called numbers.

Step A is an exercise in elementary combinatorics involving binomial coefficients, while step B is the one that requires some more thought.

Consider first the case j=3, where three of the nine squares are marked. Since each row is formed by three squares, three out of the 84 patterns made up by three marks will qualify, so the sought probability is 3/84 or 1/28. When j=4, out of the 126 different patterns, the qualifying ones are those where three marks cover one of the three rows while the outlier may end up in any of the six remaining positions. Thus 3*6/126=1/7 is the number we are looking for. The case j=5 is similar, three of the marks cover one of the three rows while the other two can be distributed freely over the remaining six squares. The number of qualifying patterns is therefore 3*15, so our probability is 5/14. The same reasoning cannot be used when j=6, however. Since the three outliers may cover a row by themselves, we would count some qualifying patterns twice, namely those which cover precisely two rows. We end up with 3*20-3=57 qualifying patterns consisting of six marks, out of a total of 84 patterns. For j>6, all patterns qualify and for j<3 there are no patterns which could ever fill an entire row. We end up with the following probability table.


Combining with the result from step A and performing similar calculations for 2 and 3 rows, we get the complete table of Bingo probabilities for this mini scale game.


Also added is a column for the probabilities of covering the four corners. In addition to the prizes paid for 1, 2, and 3 row Bingo, we could maintain a progressive jackpot funded by 5% of all bets and paid when a ticket fills the corners within 5 called numbers. The average pot when hit is about $60 if the ticket price is $1, and it occurs once every 1200 tickets sold, on average.

Note that, as a byproduct of these calculations, we have the base for a player vs. bank type of Bingo game, where the probabilities are a prerequisite when stitching the win table together.

In the full scale case, where each ticket has 25 squares with numbers between 1 and 75, it is of course inconvenient to do the calculations in step B by hand. I would normally write a computer program working with bit operations, where one bit is assigned to each square in the grid. In a for loop, we let an integer mask range from 0 to 2^25-1. In each step, the number of bits set is our j. If the integer p is the bitmask for a certain win pattern, e.g. a row, we increment the appropriate counters when p&~mask=0. Here, & denotes bitwise AND while ~ denotes bitwise NOT. The code may look something like this.