It’s been too long since I last wrote here! So much has happened in the world that I’ve been a little distracted - my Nationals winning the World Series, the House launching impeachment proceeding over the Ukraine scandal, California wildfires - it’s a crazy time.
One undeniably positive development over the last couple weeks has been the return of the NBA, which is about 10 games into the season today. To celebrate the beginning of the season, and dip my toes back into a little sports data, I wanted to carve out some time to dig into the numbers and see what they might tell us about this first chunk of the season.
Team Efficiency Trends
The chart below shows the performance of teams so far this season on the basis of their offensive and defensive ratings, straight from the NBA’s advanced stats portal. A higher offensive rating indicates that the team is more proficient at scoring, and is a positive, while a lower offensive rating suggests that points are harder to come by. Notably, the inverse is true for defense - a higher rating there implies the defense is unable to stop the offense, while a lower defensive rating means the team is proficient at slowing down opponents.
A few takeaways from the data:
- Both Los Angeles teams, the Lakers and Clippers, are obviously huge stories this season due to their acquisitions of Anthony Davis and Paul George and Kawhi Leonard, respectively
- The Clippers fit nicely into the top right quadrant of our chart, pairing a solid defense with one of the best offenses in basketball
- The Lakers clock in a bit below average on offense, but with the best defense in basketball by a good margin
- The Suns and Pacers shockingly slide in alongside talented teams from Boston, Milwaukee, and Toronto on the strength of above-average offense and defense
- The Warriors have been an absolute dumpster fire on defense with no Klay, KD, or (now) Steph
- Luka and Kristaps have powered the Mavericks into the best offense in the league, but Tim Hardaway, Seth Curry, Dwight Powell, Maxi Kleber, and J.J. Barea have stepped up their collective game as well
Here’s another view of the same data which shows the spread between each team’s offensive and defensive rating, as well as how each rating lines up against the rest of the league as a whole. Nothing else in particular to add here, but it is striking to see the difference between the Laker’s fantastic defensive rating and the Warrior’s - practically polar opposites for teams that are scoring the ball at more or less the same rate.
With all respect to Ivica Zubac, who is benefiting from some great stats in limited minutes on a great Clippers team, but doesn’t really fit here, this chart shows a real who’s who of NBA stars. After a few tough years, it’s great to see Kevin Love showing up here and for the Cavs too.
Team Offensive Trends
The correlation matrix below is a fun twist on the scoring data provided by NBA Stats, which encapsulates metrics like the percentage of shots taken by a team which are two pointers, percentage of shots being assisted or unassisted, etc. What I’m particularly interested in is observing how strongly different variables are correlated with Wins (W).
While it doesn’t look like any variables have a particularly strong correlation with Wins (yet, perhaps?), it is fun to see what is generally positive or negative - in a nod to Daryl Morey and the modern NBA, the metric most negatively correlated with Wins is the percentage of points coming from mid-range two pointers, while the metric most positively correlated with Wins is the percentage of field goals attempted from three.
The final topic I’ll dig into, which I’ve covered before, is RIM protection. I like to use a metric I’ve concocted called
RIMD to measure rim protection, because it bakes in both the effectiveness of the defender (as measured by the shooting % of opponents relative to their shooting baseline) and normalizes by the volume of shots defended (since a high amount of
DFGA means the player can impact many shots over the course of the game, and high volume should be appropriately rewarded or punished).
RIMD = [FGA_DIFF * DFGA] / LEAGUE_AVG_DFGA