March 1st, 2017 at 11:00:47 AM
permalink

Hello everyone and Wizard,

I've been tasked at work to analyze a new bingo game. I have a couple of questions regarding coverall/blackout bingo (all 24 numbers + 1 free space needs to be dabbed). I would appreciate it if anyone could confirm that the following statements are true.

1) the cumulative distribution function of number of calls needed for coverall/blackout (with only 1 bingo card in play) can be modeled by the probability mass function of the hypergeometric distribution (as it can in Keno).

2) for multiple distinct cards in play, say n, can we use the following formula: 1-(1-p)^n to model the cumulative distribution function of number of calls where p is the probability of a single card achieving coverall?

As for 2, the statement is contradictory to Wizard's website; please refer to the Multi-Player Bingo section (https://wizardofodds.com/games/bingo/probabilities/2/). I agree with Wizard that the formula does not hold when you try to model anything other than coverall/blackout. However, I believe the formula is valid when we are modeling coverall/blackout game. I'd be curious to hear if anyone agrees with me.

I've been tasked at work to analyze a new bingo game. I have a couple of questions regarding coverall/blackout bingo (all 24 numbers + 1 free space needs to be dabbed). I would appreciate it if anyone could confirm that the following statements are true.

1) the cumulative distribution function of number of calls needed for coverall/blackout (with only 1 bingo card in play) can be modeled by the probability mass function of the hypergeometric distribution (as it can in Keno).

2) for multiple distinct cards in play, say n, can we use the following formula: 1-(1-p)^n to model the cumulative distribution function of number of calls where p is the probability of a single card achieving coverall?

As for 2, the statement is contradictory to Wizard's website; please refer to the Multi-Player Bingo section (https://wizardofodds.com/games/bingo/probabilities/2/). I agree with Wizard that the formula does not hold when you try to model anything other than coverall/blackout. However, I believe the formula is valid when we are modeling coverall/blackout game. I'd be curious to hear if anyone agrees with me.

March 1st, 2017 at 6:34:09 PM
permalink

Using the HGD provides a close estimate. For the true probabilities, you need to consider that not all distributions of X calls are equal, and the distribution is something that all cards in play are subject to.

So you have to split the calculation into two parts. Let's say you want the probability of a coverall in X calls (or less) when Y cards are in play:

1) Identify (iterate through) every possible distribution of X calls. For example, with 50 calls, there are 20,176 possible distributions (including distributions where a coverall is not possible). Determine the probability of each distribution.

Then, for each distribution:

2) Determine the probability of achieving a coverall given the current distribution. This will of course be zero when there are fewer than 4 Ns or 5 Bs/Is/Gs/Os.

3) Apply the 1-((1-p)^{Y}) formula here with p = the result of #2 and Y = the number of cards in play.

4) Multiply the result of #3 by the distribution probability of #1, and accumulate (sum) these results for each distribution to determine the overall probability of a bingo within X calls or less for Y cards.

For example, for a coverall in 50 calls, here are the true probabilities (vs. the HGD estimates) for a few card quantities:

1 card = 0.0000047150811362 (vs. the HGD estimate of 0.0000047150811337)

100 cards = 0.00047138 (vs. the HGD estimate of 0.00047140)

500 cards = 0.00235428 (vs. the HGD estimate of 0.00235477)

1000 cards = 0.00470206 (vs. the HGD estimate of 0.00470399)

5000 cards = 0.02325221 (vs. the HGD estimate of 0.02329973)

The above calculations assume the following:

- standard North American bingo cards are used (5 Bs, 5 Is, 4 Ns, 5 Gs, 5 Os)

- the cards in play are random

- the numbers are drawn randomly

So you have to split the calculation into two parts. Let's say you want the probability of a coverall in X calls (or less) when Y cards are in play:

1) Identify (iterate through) every possible distribution of X calls. For example, with 50 calls, there are 20,176 possible distributions (including distributions where a coverall is not possible). Determine the probability of each distribution.

Then, for each distribution:

2) Determine the probability of achieving a coverall given the current distribution. This will of course be zero when there are fewer than 4 Ns or 5 Bs/Is/Gs/Os.

3) Apply the 1-((1-p)

4) Multiply the result of #3 by the distribution probability of #1, and accumulate (sum) these results for each distribution to determine the overall probability of a bingo within X calls or less for Y cards.

For example, for a coverall in 50 calls, here are the true probabilities (vs. the HGD estimates) for a few card quantities:

1 card = 0.0000047150811362 (vs. the HGD estimate of 0.0000047150811337)

100 cards = 0.00047138 (vs. the HGD estimate of 0.00047140)

500 cards = 0.00235428 (vs. the HGD estimate of 0.00235477)

1000 cards = 0.00470206 (vs. the HGD estimate of 0.00470399)

5000 cards = 0.02325221 (vs. the HGD estimate of 0.02329973)

The above calculations assume the following:

- standard North American bingo cards are used (5 Bs, 5 Is, 4 Ns, 5 Gs, 5 Os)

- the cards in play are random

- the numbers are drawn randomly

Last edited by: JB on Mar 2, 2017

March 2nd, 2017 at 8:47:20 PM
permalink

JB's answer sounds right to me. If you know the probability of covering any given pattern in x calls is y for one card, you can't assume is it 1-(1-y)^n for n cards. This is because the cards are correlated. All of them have 5 B's, 5 I's... If there is a smooth distribution of columns called, then all of them are more likely to hit early. I've seen it happen lots of times where it takes a long time for one letter to get called. When it finally does, a ton of people call BINGO.

The easiest way to do multi-card bingo math is by random simulation. I know it isn't as elegant as a closed forum answer, but sometimes the easiest way is ... the easiest way.

The easiest way to do multi-card bingo math is by random simulation. I know it isn't as elegant as a closed forum answer, but sometimes the easiest way is ... the easiest way.

It's not whether you win or lose; it's whether or not you had a good bet.

March 3rd, 2017 at 7:44:22 AM
permalink

Hello Wizard, JB,

Thank you for your responses. Indeed, I had not considered the fact that there could be instances where only 4 B's have been called in a given number of calls and there is no coverall bingo possible. I understand now why the cards are correlated.

One of the variants of the new game we are contemplating does not have the column restrictions, i.e. any numbers between 1 and 75 can go anywhere in the 5x5 matrix. I believe HGD works for this game as it is really Keno but in Bingo format.

Cheers,

Thank you for your responses. Indeed, I had not considered the fact that there could be instances where only 4 B's have been called in a given number of calls and there is no coverall bingo possible. I understand now why the cards are correlated.

One of the variants of the new game we are contemplating does not have the column restrictions, i.e. any numbers between 1 and 75 can go anywhere in the 5x5 matrix. I believe HGD works for this game as it is really Keno but in Bingo format.

Cheers,

- Jump to:
DEFUNCT CASINOS Bill's Gambling Hall & Saloon MonteLago O'Sheas Sahara Western FORUM INFO Announcements Help Rules GAMBLING Betting Systems Big Wins Blackjack Craps Dice Setting Gambling with an Edge Online Gambling Other Games Poker Slots Sports Betting Table Games Trip Reports Video Poker GAMBLING OUTSIDE VEGAS Asia Atlantic City California Eastern U.S. Europe/Africa Mississippi Nevada (other) Oceania The Americas Western U.S. GAMING BUSINESS Boyd Gaming Caesars Entertainment Game Inventors Corner MGM/Mirage Other Sands Station Casinos Wynn LAS VEGAS ATTRACTIONS Night Clubs Other Attractions/Entertainment Relaxation and Rejuvenation Shopping Shows Strip Clubs Thrill Seeking LAS VEGAS CASINOS Aliante Casino Aria Arizona Charlie's Casinos Bally's Barcelona Bellagio Binion's Boyd Gaming Casinos Caesars Palace Cannery Casinos Casino Royale Casuarina Circus Circus Cosmopolitan D Las Vegas El Cortez Ellis Island Excalibur Flamingo Four Queens Golden Gate Golden Nugget Hard Rock Hilton Hooters Jean/Primm Casinos Longhorn Casino Luxor M Mandalay Bay MGM Grand Mirage Monte Carlo New York, New York Palms Paris Planet Hollywood Plaza Poker Palace Quad, The Rampart Rio Riviera Silver Nugget Silver Sevens Silverton Skyline Small Casinos South Point Station Casinos Stratosphere Treasure Island Tropicana Tuscany Vegas Club Venetian and Palazzo Wynn and Encore OFF-TOPIC Adult Discussions Free Speech Zone General Discussion GLBT Corner Gripes Kiosk Off-Topic Other Casinos Religion QUESTIONS AND ANSWERS Advice All Other Casual Corner Gambling Las Vegas (other than gambling) Math

© 2009-2017 Michael Shackleford
My other sites: Wizard of Odds, Wizard of Macau, Las Apuestas