Context

The dataset contains information about NBA-Player statistics of the regular seasons 2016/17, 2017/18 and 2018/19. The goal here is to have all NBA-Player statistics of the past three seasons under one umbrella so that it is easy for everyone who is interested in sports analytics and especially basketball to start their Data Science Journey. I want to motivate you using this and perhaps other external datasets for your analysis. I'm excited to see the resulting notebooks.

Content

The dataset contains three csv-files corresponding to the three different seasons. Each file has the same 30 columns. It includes columns like:

• Player Name
• Player Position (PG, SG, SF, PF, C; no multiple positions)
• Player Team (If a player has more than 1 row with different teams then this means that the Player got traded during the season. An additional row with total stats of the season is provided in these cases)
• Minutes played per game
• Made field goals, Attempted field goals (both per game) and field goal percentage
• Made three-pointers, attempted three pointers (both per game) and three-point percentage
• Same for two-pointers and free-throws
• Offensive, defensive and total rebounds per game
• Assists, steals, blocks, turnover, personal fouls and points (all per game)

Acknowledgements

I scraped the dataset from Basketball Reference. I want to thank them for providing us with it.

Inspiration

Here are some ideas:

• Basic analysis including descriptive and inferential statistics using nice data visualization.
• Prediction models using other external datasets.