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Описание: In order to use Splunk software to analyze Blackjack data we first need data. I generated that data using a Blackjack simulator I wrote for this blog post. You can find that simulator, the data we will use for the analysis and the Splunk dashboard code here.

The data we will be working with is in blackjack_simulation_files.zip (direct link). If you do not have Splunk entitlements and want to try things out with the provided data, you can use the Docker-Splunk project here.

While a treatise on the inner workings of the simulator code is out of scope, we should take a moment to describe what exactly was being simulated. Blackjack can be played with many rule variations. In this case we set up a game of Blackjack wherein:

Blackjack pays 3:2

The shoe has six decks

Player is permitted to double down on any first two cards

Player is permitted to re-split to up to four hands

Player is permitted to surrender

Additionally, the simulator employed seven player agents, each behaving differently. All but Player 7 employed perfect Basic Strategy. Player 7 was programmed to only buy into the hand and never take any cards. Players 2 to 6 were programmed to count cards. The players that counted cards did so according to different techniques and bet spreads — meaning they varied their bet depending on the degree to which their counting scheme indicated they had an advantage.

Here is a breakdown of all the player agent behavior:

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