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It appears that whatever strategy that runs first in the simulation will result in wildly different values in the beginning. About Help Legal.{/INSERTKEYS}{/PARAGRAPH} How to process a DataFrame with billions of rows in seconds. Written by Marco Santos Follow. Make sure that this pickle file is in the same folder as the Blackjack code in order for it to run properly. 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. This option is what we will be demonstrating in order to determine the most effective card counting strategy. Marco Santos Follow. Running this code will give us the following graph:. Then, we added card counting functions to keep track of the count while the game is playing:. Now that we have all of our functions ready, we can run Blackjack. Closing Thoughts As it appears in the graphs before, each strategy can provide a decent edge over the dealer. But, card counting can provide you with an edge and it really does not matter which strategy you choose to stick with. Feel free to test out the Blackjack game in your own terminal or IDE. This function may require some tweaking to better improve results later on. Well, one option we could do is to implement each strategy ourselves, go and play Blackjack several times, then record the results. Next, in order to count cards during the game, we created a Pandas DataFrame of the different card counting strategies and their specific values for every card:. 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. This also seems to provide a decent percentage of success as long as the strategy is followed with no deviations. Beating the Dealer with Programming. To keep things simple, we would leave out options such as splitting , doubling down , surrendering , etc. Each function serves an important purpose for running the game. 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. You can either beat the dealer, lose to the dealer, or tie with the dealer. 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. Sign in. There are two versions of this game:. 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. A Medium publication sharing concepts, ideas, and codes. The outcomes of Blackjack are very straightforward. It is important to note that these card counting strategies at most, give a 0. The goal is simple; just try to get as close to the value of 21 as best as you can without going over. You signed out in another tab or…. But the overall results for every strategy are very similar. Become a member. Now, we just need to graph the results from our simulations. All in all, good luck to those who decide to use these strategies! See responses 7. 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. Towards Data Science A Medium publication sharing concepts, ideas, and codes. Many different strategies for card counting exist and these strategies implement different values for each card. Chris in Towards Data Science. 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. Another option can be to code out a game of Blackjack, simulate the game, then record the results after a desired number of simulations. As it appears in the graphs before, each strategy can provide a decent edge over the dealer. It should be noted that we do not endorse gambling as a method of making money. Roman Orac in Towards Data Science. Also, we included draws with our wins because a draw in Blackjack results in no money lost when playing against just the dealer. Card counters use this count to determine whether to hit or stay depending on whether the count is high or low. For example, one strategy may count the Ace as -1 and another strategy will count it as 0. Chanin Nantasenamat in Towards Data Science. Jun in Towards Data Science. This can be done simply by plotting the results for each strategy in a line graph format using Matplotlib. Towards Data Science Follow. With that handled, we can move on to simulating the games. Card counting may appear difficult at first, but it is actually quite simple. Using Card Counting in Blackjack Card counting may appear difficult at first, but it is actually quite simple. 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. More From Medium. These functions keep track of the count throughout every round of Blackjack in the entire game. We shuffled the order of the strategies to be simulated to further increase the randomness. Implementing either one of these strategies seems to be enough to give you an advantage over the casino or house. We reiterate that each strategy is reported to give the player a 0. However, betting size in a normal Blackjack game is important to know. Julia Nikulski in Towards Data Science. So what if we wanted to implement a card counting strategy into our Blackjack games? You signed in with another tab or window. For the game of Blackjack, that is all it takes. Emmett Boudreau in Towards Data Science. In this code to create a DataFrame of card counting values, we exported a pickle of the DataFrame for use later on. This function follows the rules of every Blackjack dealer. Make Medium yours. Also, since we are measuring wins versus losses, we can eliminate the need for betting. No one wants to lose and losing in Blackjack can hurt depending on your bet size. Then, you add them all together and this total value becomes the count. {PARAGRAPH}{INSERTKEYS}B lackjack is one of the simplest games to play at a casino. We begin the simulation by entering our function for playing Blackjack games into a loop that will iterate through a list of strategies and then play 1, games with each strategy. It appears that most of the card counting strategies have similar results but they all seem to beat out having no strategy at all. However, we must temper our expectations for each strategy. Also, please know that these simulations and results were made with relatively simple Python methods and tools. That option can be extremely time consuming and inaccurate in actually showing the probability and effectiveness of the strategy. There are many more differences between the strategies than just the card values but we cannot cover them all. Which one should we choose? So our observation was correct in assuming that whatever strategy ran first results in erratically different values. Finally, we have simulated over 1, games of Blackjack for each different strategy we have listed in the Pandas DataFrame. It deals until the dealer reaches a value between 17 to 21 or until the dealer busts. It eventually compares the hand of the dealer to the hand of the player to determine who won. 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 is also one of the easiest games to learn. Discover Medium.