/nba_3-pt_analysis

COGS 108: Data Science in Practice (UC San Diego Fall 2022)

Primary LanguageJupyter Notebook

The Weight of the 3-Pointer in the Modern NBA

COGS 108- Data Science in Practice Fall 2022 Project

Team Members: Jackson Conte, Andrew Nguyen, Anish Rajeshkumar, Baraa Zekeria

For our project, we decided to explore whether or not the proportion of 3 point shots overall affected playoff success for NBA teams in the last 20 years. To do so, we pulled information from the NBA api from past games of every NBA Team and exploring trends for 2 point field goals and 3 point field goals. For our data analysis, we decided to quantify playoff success and separate our data set to perform on a Kendall-Tau Test on. In doing so, we could see if our hypothesis stands true for one era or multiple eras.

Project Video

├── data
│   ├── nba_stats_cleaned.csv
│   ├── nba_stats_data_dictionary.csv
│   ├── nba_stats_raw.csv
├── .gitignore
├── DataCheckpointGroup_018-Fa22.ipynb
├── EDACheckpointGroup_018-Fa22.ipynb
├── FinalProjectGroup_018-Fa22.ipynb
├── README.md
├── ProjectProposalGroup_018-Fa22.ipynb
└── nba_shots_analysis_018-Fa22.pdf

Note:

  • The FinalProjectGroup_018-Fa22.ipynb is the updated version of all of the XXXCheckpointGroup_018_Fa22.ipynb notebook files compiled together