Create an NBA Game Simulator with Monte-Carlo Method using R Studio
An Overview of an Undergraduate Statistics Project: Building an NBA Game Simulator with Monte-Carlo Method in R Studio
Link to Simulator:
Project Description:
This article provides an overview of a statistics project that involves building an NBA game simulator using the Monte-Carlo method in R Studio. The Monte-Carlo method is a statistical technique that uses random sampling to simulate complex systems. In this project, I apply this method to create a simulator that predicts the outcome of NBA games based on various team and player statistics.
To implement this simulator, I use R Studio, an open-source integrated development environment (IDE) for the R programming language. R is a popular language for statistical computing and graphics, and its libraries offer numerous statistical functions and data visualization tools that are useful in this project.
Through this project, I aimed to explore the applications of statistics in simulating real-world scenarios and enhanced my understanding of the underlying statistical concepts. Additionally, this project serves as a practical demonstration of the use of R Studio for statistical analysis and simulation.
This project was done as a final project for a semester-long course, Statistical Computing in R. To gain access to the R files, please email thetopphotoshop@gmail.com
Links to Articles on how the simulator was built:
Original Write-Up (PDF):
