Using Data Analytics to Choose Winning Casino Games

If you are a casino player, you are probably wondering how to increase your chances of winning at games. This can be a popular slot machine like Sweet Bonanza or a classic card game. In any case, we are sure that you have heard lots of strategies so far, such as card counting or progressive betting. How about data analytics? This means collecting and analyzing data to gain information in pursuit of making better decisions. It is used as an effective technique in many industries and can be adapted to casino games too. Below, we will explain how.

Types of Casino Games

Casino games can be divided into two main categories: skill-based games and chance-based games. Skill-based games require skill or knowledge – for example, blackjack or poker. Chance-based games, on the other hand, require nothing but luck. For example, roulette or slot machines.

The main difference between them is the “house edge”. The house edge simply shows how much profit the casino will make on your bets in the long run. Basically, the lower it is, the better for you as a player.

• For example, the house edge of blackjack is around 0.5%. This means that for every 100 units wagered, the casino can make a profit of 0.50 units on average. 
• Slot machines, on the other hand, have a higher house edge, somewhere between 5% and 8%. So, for every 100 units wagered, the casino can win 5-8 units.

Volatility is another difference between skill-based and chance-based games. It measures how much the outcomes can vary from the expected value. The higher it is, the results will be more unpredictable. Chance-based games have higher volatility. For example, roulette has high volatility, so its outcomes (your wins and losses) can vary widely between each round.  Blackjack (and skill-based games), however, has low volatility, so the outcomes are more consistent and predictable.

Data Analytics for Casino Games

So, how can data analytics help you? Well, by using this technique, you can choose winning casino games by measuring and comparing the expected value and variance of them. The “expected value” is a term that refers to the average amount that you can expect to win or lose in the long run. The variance, on the other hand, can show how much the outcomes vary from the expected value.

To find out what the expected value and variance of a casino game are, you need to know the probability of each outcome, the payouts, and the amount of your wager. 

• For example, let’s say we are playing the European variant of roulette. Let’s place a bet of 10 units on black. The probability of this outcome is 48,65% (18/37), and you can win 2x your bet (the payout).
• The formula for the expected value is (probability x payout x bet) – bet
• So, (0.4865 x 2 x 10) – 10
• -0.27 (expected value).

This shows that for every 10 units you place on black, you can expect to lose 0.27 units on average.

But we need to know the variance too, right? We can the formula below for that: 

• probability x (payout x bet – expected value) ^2
• So, 0.4865 x (20 – (-0.27)) ^2
• 97.86 (variance)

This shows that we can expect a deviation of 97.86 units from the expected value for every 10 units we place on black. 

Data analytics can help us to compare different casino games by calculating their expected value and variance. We can simply choose the ones that have a higher expected value and a lower variance. For example, if we play blackjack instead of roulette, the house edge will be 0,50% on average. Using the formulas above, we can calculate the expected value as -0.05 per 10 units bet. The variance, on the other hand, will be around 1.2 per 10 units bet. So, blackjack has a higher expected value and a lower variance. This shows that it is a better game than roulette, in regard to profitability.

Data Analytics for Bankroll Management 

Data analytics can also help us to manage our bankroll. We can manage your money more effectively and set limits on how much we can afford to lose. Kelly criterion is one of the most popular data analytics tools we can use. It is a formula that shows how much we should bet on each outcome, based on the size of our bankroll. The formula is this: 

• (probability x payout) – 1 / (payout – 1)

For example, let’s use this formula on roulette, and once again, place a bet on black. The probability is 48,65% and the payout is 2x. So:

• (0.4865 x 2) – 1 / (2 – 1)
• -0.027

The result looks very similar, right? However, this time it shows us what our wager amount should be for this bet. Simply put, it says to use -0.027% of our budget on this bet. And yes, this also means “do not place a bet”, because the result is negative. This is not surprising, because the Kelly criterion shows us we will lose money in the long run, and this bet should be avoided. 

How about blackjack? In a game played with a single deck, our chance of winning is roughly 49% for a 2x payout. So:

• (0.49 x 2) – 1 / (2 – 1)
• 0.02

This time the result is positive, and it says “use 2% of your bankroll as your wager amount”. The Kelly criterion can help us to determine the optimal wager amount for different casino games, but you should remember that it has some limitations too. For example, the formula assumes that you know the probability and payout of each possible outcome. It also assumes that you have an infinite bankroll. Both scenarios are quite unlikely in real life.  So, this formula should only be used as a guideline: make sure to adjust it to your experience level and budget, instead of using it as a “fixed rule”.