Game Data Analysis – Tools and Methods by Coupart Thibault

By Coupart Thibault

This publication seems on the most dear key functionality signs utilized in games after which highlights the strengths and weaknesses of alternative recommendations which are to be had which will acquire your info. The e-book will eventually clarify the type of research you must practice in accordance the content material of your video game.

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Initially, statistical laws and distributions appeared with the study of gambling games. The motivation behind those studies was to improve the chances of winning. Concretely speaking, laws are a theoretical assumption, an expectation of how structured a set of numbers should be. • The normal distribution (also called Gaussian distribution): It corresponds to a continuous probability distribution that takes the form of a bell curve when all of the data points are displayed on a chart. Concretely speaking, the center will contain the highest number of a value and correspond to the highest point of the bell curve, whereas values on extremities decrease quickly on either side.

Through queries and joins, you are able to retrieve, filter, and calculate data with a lot of freedom. Notice that while SQL refers to the language used, storage solutions based on SQL are numerous: MySQL, Oracle, Microsoft SQL server, Microsoft Access, and the list goes on. Currently, the only open source solution is MySQL, and you can download it for free on the Web. Environment and Tools for Data Analysis Another important feature in SQL is the server-replication facility. One server can be duplicated and have several identical slaves.

Average revenue per users: This KPI shows the amount of money gained for one user (paying or not). • Lifetime value: This KPI is supposed to show the total amount of revenue generated by one user considering the current average revenue per the paying users’ KPI of your game and the retention expectancy. As we will see later, this KPI is hard to calculate because it is always evolving, but it remains very important in order to estimate if an acquisition campaign is worth its cost or not. [ 24 ] Chapter 2 • Conversion rate: This KPI shows the number of non-paying users who have become paying users.

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