NBA 4th Quarter Analysis: Project Overview

• Compares the first three quarters with the last quarter --> fewer points in the 4th quarter are a result of slower pace (fewer possessions), not because of more defensive intensity
• Scraped the games and box score stats of the 2021/2022 season
• Engineered advanced stats from the traditional stats
• Visualized different stats and trends in specific game situations
• Made a 2-sample t-test to prove my observations
• KMeans clustering --> the top teams can elevate their game in the 4th quarter

Code and Resources Used

• Python Version: 3.7
• Packages: Pandas, NumPy, Sklearn, Matplotlib, Seaborn, Selenium, sciPy
• Data: https://www.nba.com/stats/

Web Scraping

Scraped four tables (1st quarter, 2nd quarter, 3rd quarter, 4th quarter), each containing:

• traditional stats, e.g. Points, +/-, Assists, Rebounds, Shooting Percentages...
• Game Date
• Matchup

Data Cleaning

For the comparison, I created new variables:

• Opponent out of Matchup
• Court (1 = home team and 0 = away team) out of Match up
• Removed season column
• Opponent stats out of the row with the right Match up
• Possessions out of FG, FGM, FTA, TOV ...
• Pace out of possessions
• Margin of victory/loss out of +/-

EDA

I looked at the distributions of the data and combined different statistics. Below are a few highlights from the pivot tables.

2-sample t-test

I tested statistics from the first three quarters to see if they're significantly different from the 4th quarter:

• Reject H0 at the 95% confidence interval for Pace, AST, 3P%,' PTS', 'FT%
• Can't reject H0 for DEFRTG and OFFRTG at the 95% confidence interval

KMeans Clustering (n_clusters=4)

I wanted to know the individual team performance if some teams step up in the 4th quarter:

• The top 2 in the season standings (i.e., PHOENIX SUNS, MEMPHIS GRIZZLIES) grouped in the same cluster
• Also, the bottom teams were all grouped in one cluster
• The other two groups were teams who are in the middle or don't improve much in the 4th quarter to be in the elite cluster

Conclusion

I couldn't prove that the defence improved in the game's last quarter. The lower scoring average in the 4th is a result of fewer possessions. Still, some teams play better in the 4th quarter, and it is not a coincidence that these are the top-ranked teams in the league. Because of that, my claim would be that the best teams have an on-switch and can play their best when it matters.