A Primer on Usage Rate
Usage rate describes the percentage of team plays used by a particular player while that player is on the court - basically, how likely a given player is to end a possession with a field goal attempt, free throws, or a turnover. This is a great indicator of how “ball dominant” a particular player is, and the degree to which a team’s central offensive player finished possessions can tell us a great deal about how that team plays on offense.
This Year’s Usage Rate Leaders
To find each team’s leader in usage rate, I first scraped the NBA stats database to get all qualified players. Then, I used a simple R script to create a dataframe which pulled the player from each team with the highest usage rate. With this information collected, I spent some time playing around with the data, looking to see if any significant takeaways might materialize…
library(readxl) library(tidyverse) library(ggrepel) library(RColorBrewer) stats <- read_excel("NBA Usage Rate_03222018.xlsx") statsbyteam <- group_by(stats, TEAM) View(statsbyteam) teamleader <- statsbyteam %>% filter(`USG%` == max(`USG%`)) teamleader <- teamleader[-c(15), ] View(teamleader)
With usage rate leaders for each team varying in age from 19 to 36, I thought it would be interesting to plot the winning percentage of each team along with the age of the team’s usage rate leader. The plot above breaks the league into four quadrants, of which I’ve identified 4 main groups of teams:
- Embracing the Tank: These are all teams with losing records which have turned the reigns over to their young players, in an effort either to develop for the future, or tank for upcoming drafts
- Young Stars: These are all teams either on the threshold of the playoffs or solidly in the playoffs, led by young stars and emerging superstars like Giannis and Embiid
- Flawed Centerpieces: These are teams led by veteran stars who can’t quite put it all together, with several right on the margin of playoff contention, or sitting outside the top 8
- Engines of Success: These are superstar-led teams having outstanding seasons
It’s particularly notable in this chart to see Joel Embiid up so high to the top corner on this chart - and indicator of exactly how good they’ve been while he’s on the court, as well as how they’ve continued to struggle on nights that he is out.
This chart splits players into quadrants based on Scoring Rate and Assist Rate. Particularly of note on this chart are John Wall and Kristaps Porzingis, who fall on nearly opposite ends of the chart. Wall, a score-first point guard, assists on over 53% of the Wizards points while on the court. Porzingis, who may or may not be allergic to passing, assists on less than 10% of the Knicks points while on the court. James Harden also stands out for his ability to both score and assist for teammates - basically his MVP case in a nutshell.