Estimating the Impact of a Player's Scoring Through Numbers (ESI)


Scoring is probably the most polarizing aspect of basketball, and that's because of just how many factors go into it. A lot of people go the classic "best combination of volume and efficiency" route to rank their best scorers, while others might value the actual scoring counters and versatility a bit more. Even then, there are other factors influencing these things, such as the team around each player, the role they are asked to play, and of course the era that they played in. I found myself struggling to really evaluate a player's scoring while keeping all of these different aspects in mind, so I developed a statistic that would give a more accurate depiction.


Estimated Scoring Impact (ESI) uses a combination of scoring volume, efficiency, team situation, and era to estimate how much value a player provides per 100 possessions from scoring alone, given an even playing field.

Well how exactly do we capture the value of one's scoring? We can start by looking at a player's actual scoring rate per 100 possessions, to get a good idea for just how much they're putting the ball in the basket. While this does give players an equal amount of opportunities to score, it doesn't gauge how difficult it is to score, which can be very dependent on the defense. Here's a quick look at the league average offensive rating by year, showing the drastic changes in how efficient offense has been over time:

To fairly account for the difference in scoring difficulty over time, we'll have to use an inflation-adjusted scoring rate.

Inflation-Adjusted Points Per 100 Possessions measure a player's scoring rate while factoring in the league average points per possession that season, giving us an actual "relative to era" scoring rate.

The next component in ESI is a player's scoring efficiency, or how accurate they are when attempting to score. This is an extremely important factor that many seem to overlook, as the more efficient a player is, the less amount of possessions they're taking up to score, thus giving their team a better chance at more productive offense. The actual measurement used for players' efficiency is Relative True Shooting Percentage (rTS%), but I did make some slight adjustments to account for role and add a slight skill curve. With the way efficiency is weighted in my model, players who are above league average get extra credit for ramping up the volume that they are attempting to score at, meaning a player who attempts 20 shots a game on 5% rTS would get more credit for efficiency than someone attempting 7 shots a game with the same accuracy. Certain teams relied on their primary scorer increasing the quantity of attempts as a source of offense (Allen Iverson, Kobe Bryant, Carmelo Anthony), and the best way to put value to that is by giving them more credit for maintaining efficiency as opposed to 3rd/4th options who are receiving easier looks. Of course the other end of the spectrum means that players with below average efficiency get taxed for ramping up the volume, as they are doing so at a below average rate.

When looking at hundreds of seasons on record, it's pretty clear that players generally become less accurate as they attempt more shots:

Those few outliers that you'll see at the top right of the graph are the ones who get the most credit for this portion of the metric, as they're capable of maintaining elite accuracy while still providing lots of volume.


Now that we've measured era-adjusted scoring rate and efficiency relative to volume, it's important to take the team situation into account. It's fairly obvious that it's scoring the basketball becomes much easier when there's more space to work with, and that's why the final input comes from my Lineup Spacing metric. This is a simple, yet effective measurement that looks at the team around a specific player and how they shoot the outside shot, relative to their era. The downside to this is that 3 point data can only go far as back as the 3 point line itself, meaning ESI only goes back to 1980.

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If you're interested in viewing the results of ESR and the best seasons on record, you can do so by becoming a member here.


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