by Baltej Parmar
Comparing players is the stock in trade of fandom. Whatever your team, everyone wants to know which player is better than his peers. Statistics allow us to compare various aspects of player performance – perhaps most notably efficiency. “Russell Westbrook has a career FG% of .434, while Stephen Curry has a FG% of .476. The difference isn’t much.” Are we sure that a difference of .042 is not much, though? The scale of statistics can make it difficult to use them responsibly in comparisons. In the example above, Curry makes 42 shots more than Westbrook out of 1,000. Since a player doesn’t take 1,000 shots in a game, it is not directly obvious how much more likely Curry’s team is to win a game based on the difference in FG%. What if we had a better way to measure how much a player’s shooting impacts the score on a game-by-game basis? That’s why I’m introducing Applied Efficiency, a new NBA stat which does just that.
The most widely-known measure of shooting efficiency is True Shooting % ( TS%), which includes the impact of 3-pointers and free throws in a player’s scoring efficiency. In our arbitrary example, Curry shoots vastly more 3-pointers than Westbrook, at a more efficient conversion rate. Curry is also a superior free throw shooter. Relative TS%, which looks at the average TS% for the league and tells us how many percentage points above or below average a player is, also appears in basketball discourse somewhat frequently. The highest-efficiency players are usually big men who only catch lobs, but they don’t get very many shot attempts since defenses are geared up to stop those attempts. Applied Efficiency combines Relative TS% and the total number of shooting possessions a player uses to show us the impact on a game-by-game basis. Scaling for attempts allows us to reflect a player’s role when measuring efficiency.
Using Applied Efficiency
Based on this method, a rating of 0.0 would be an average efficiency player. This rating system is not intended to determine which player is better than another, but merely to evaluate the scoring impact within a game of each player. It is showing us the ‘points value’ of a player’s shooting efficiency. Looking at the chart below (as of Dec 13 2019), the player who has the most impact with his scoring on a game-by-game basis is James Harden. Harden is generating 4.55 more points than an average-level player would generate if Harden’s 30.56 shooting possessions were redistributed. Also of note is Rudy Gobert, a surprising #6 on the list. Gobert mainly functions as a rim roller and needs other players to get him the ball as he’s rolling to the rim. In the 10.69 possessions a game he does get the ball to put up a shot, however, he does so at such an efficient rate that his impact is extremely high.
Gobert ranks higher than #15 Damian Lillard, but that does not mean he’s more valuable than Lillard on offense. Since Gobert can’t create his own shot and can’t create for others, he isn’t someone a team would build their offense around. His skillset is extremely valuable to Utah, but Lillard’s much broader skills would be useful to basically every team in the league. Getting Gobert more of the types of shots he takes would clearly be hugely beneficial to the team, but there are constraints which prevent any team from getting 30 lobs a game.
Even adjusting for volume, a number of the most impactful performers are dunkers and low-volume three-point snipers (plus Aron Baynes, who is somehow both). While win-counters might be quick to dismiss Brandon Ingram’s performance this season as an accumulation of empty stats, he is currently providing well above average scoring value.
The Least Efficient Scorers
Below we can see the 30 least impactful players in the league based on their shooting possessions.
There are many young players near the bottom of the table, but some names stand out. Russell Westbrook’s 22.48 shooting possessions/game are having the 7th worst impact within the league this year. If we assume average-quality teammates, Houston would be much better off having him cut down some of his attempts and redistribute those attempts to other players on the team. Westbrook brings value in other ways, but his overall inefficiency could be having a negative effect on the team. In order to confirm whether or not this is true, it would be necessary to conduct an examination of Westbrook’s teammates to evaluate the likely outcome of redistributing his shooting possessions.
Another high-volume player that is interesting in this regard is Jayson Tatum, whose 19.95 shooting possession per game are 1.64 points less valuable than league-average efficiency. Since Tatum’s teammate Gordon Hayward is operating at higher than average efficiency thus far, it will be interesting to see whether or not the Celtics shift some of their play calling toward freeing Hayward as the season goes along.
Applied Efficiency compares a player’s shooting efficiency to league average, then scales it for his volume. This means that if a player’s efficiency is affected by his volume, the metric will struggle to value such a player. As such, it is advisable to use Applied Efficiency as a description of a player’s scoring impact within his role. Players with limited skill sets may still be efficient in their role (as with the example of Rudy Gobert). By contrast, even a highly skilled player may be below the league average efficiency level due to the weight placed on him (a la Blake Griffin and Jayson Tatum).
One thing that remains to be researched is the effect of changing a player’s volume. Since changes in observed usage commonly follow changes in talent, it is difficult to conduct a natural experiment to test the hypothesis that a high-efficiency player could increase his usage or that a high-usage, low-efficiency player could improve his efficiency by shooting less.
Notes: This data will be available on greekgodofstats.com in the near future. This method is very similar to David Locke of Locked on Sports, but his numbers are proprietary and not available to the public. Listen to his podcasts (Locked on NBA and Locked on Jazz) for great basketball analysis.