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Now that we have a Blackjack game coded out and ready to go, we can finally begin simulating Blackjack games with different card counting strategies 1, times each. Implementing either one of these strategies seems to be enough to give you an advantage over the casino or house. Chris in Towards Data Science. With that handled, we can move on to simulating the games. Also, please know that these simulations and results were made with relatively simple Python methods and tools. But the overall results for every strategy are very similar. Beating the Dealer with Programming. Using Card Counting in Blackjack Card counting may appear difficult at first, but it is actually quite simple. However, the weight of those outcomes is entirely up to you because you can risk to lose a lot of money in just one hand. This function follows the rules of every Blackjack dealer. But, card counting can provide you with an edge and it really does not matter which strategy you choose to stick with. It deals until the dealer reaches a value between 17 to 21 or until the dealer busts. Roman Orac in Towards Data Science. You signed out in another tab or…. In order to tilt the odds against the casino or the house, Blackjack players have developed numerous card counting strategies to decrease their chances of losing. Many different strategies for card counting exist and these strategies implement different values for each card. As it appears in the graphs before, each strategy can provide a decent edge over the dealer. See responses 7. To simulate a Blackjack game with our code, we will have to alter our previous Blackjack code to compensate for the lack of player input. Make Medium yours. That option can be extremely time consuming and inaccurate in actually showing the probability and effectiveness of the strategy. You signed in with another tab or window. The outcomes of Blackjack are very straightforward. Which one should we choose? It appears that most of the card counting strategies have similar results but they all seem to beat out having no strategy at all. More From Medium. This can be done simply by plotting the results for each strategy in a line graph format using Matplotlib. A Medium publication sharing concepts, ideas, and codes. We reiterate that each strategy is reported to give the player a 0. There are two versions of this game:. Discover Medium. Make sure that this pickle file is in the same folder as the Blackjack code in order for it to run properly. Now, we just need to graph the results from our simulations. All in all, good luck to those who decide to use these strategies! Then, we added card counting functions to keep track of the count while the game is playing:. For the game of Blackjack, that is all it takes. So what if we wanted to implement a card counting strategy into our Blackjack games? This option is what we will be demonstrating in order to determine the most effective card counting strategy. We shuffled the order of the strategies to be simulated to further increase the randomness. Then, you add them all together and this total value becomes the count. However, betting size in a normal Blackjack game is important to know. Julia Nikulski in Towards Data Science. Also, since we are measuring wins versus losses, we can eliminate the need for betting. We recorded the last 10 rounds of each game in order to capture the effectiveness of each strategy because those rounds will have a decent count from which a decision could be made. There are many more differences between the strategies than just the card values but we cannot cover them all. Finally, we have simulated over 1, games of Blackjack for each different strategy we have listed in the Pandas DataFrame. It should be noted that we do not endorse gambling as a method of making money. However, just know that these simulations were done with a basic hit or stay decision and some of these strategies do actually factor in bet size as well as other factors. It eventually compares the hand of the dealer to the hand of the player to determine who won. Each function serves an important purpose for running the game. Towards Data Science Follow. Simulating 1, Games of Blackjack Now that we have a Blackjack game coded out and ready to go, we can finally begin simulating Blackjack games with different card counting strategies 1, times each. Chanin Nantasenamat in Towards Data Science. This function may require some tweaking to better improve results later on. The goal is simple; just try to get as close to the value of 21 as best as you can without going over. First, in order to simulate a game of Blackjack, we would need to code out a Blackjack game with all the necessary rules and regulations that come with it. Card counters use this count to determine whether to hit or stay depending on whether the count is high or low. By simulating the various different strategies, we can narrow down the preferred method of card counting that will benefit us in the best way possible. Closing Thoughts As it appears in the graphs before, each strategy can provide a decent edge over the dealer.

B lackjack is one of the simplest games to play at a casino. This also seems to provide a decent percentage of success as long as the strategy is followed with no deviations.

Another option can be to code out a game of Blackjack, simulate the game, then record the results after a desired number of simulations. Now that we have all of our functions ready, we can run Blackjack.

It is important to note that these card counting strategies at most, give a 0. Become a member. We begin the simulation by entering our function blackjack database playing Blackjack games into a loop that will iterate through a list of strategies and then play 1, games with each strategy.

Marco Santos Follow. So our observation was correct in assuming that whatever strategy ran first results in erratically different values. Sign in. For example, one strategy may count the Ace as -1 and another blackjack database will count it as 0. To keep things simple, we would leave out options such as splittingdoubling downsurrenderingetc.

Also, we included draws with our wins because a draw in Blackjack results in no money lost when playing against just the dealer. Running this code will give us the following graph:. No one wants blackjack database lose and losing in Blackjack can hurt depending on your blackjack database size. Towards Data Science A Medium publication sharing concepts, ideas, and codes.

Written by Marco Santos Follow. It is also one of blackjack counting simulation software easiest games to learn. Next, in order to count cards during the game, we created a Pandas DataFrame of the different card counting strategies and blackjack database specific values for every card:.

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These functions keep track of the count throughout every round of Blackjack in the entire game. It appears that whatever strategy that runs first in the simulation will result in wildly different values in the beginning. However, we must temper our expectations for each strategy. In this code to create a DataFrame of card counting values, we exported a pickle of the DataFrame for use later on. Well, one option we could do is to implement each strategy ourselves, go and play Blackjack several times, then record the results. How to process a DataFrame with billions of rows in seconds. Feel free to test out the Blackjack game in your own terminal or IDE. Emmett Boudreau in Towards Data Science. You can either beat the dealer, lose to the dealer, or tie with the dealer. Card counting may appear difficult at first, but it is actually quite simple. Jun in Towards Data Science.