The Highs And Lows Of Being A Top Ranked NBA 2K League Player

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The NBA is filled with great, young talent under 23 years old. Recently, Dunc’d On completed their annual top-10 NBA prospect podcast which led to many variations being posted on Twitter. Using those lists as my basis, I used my player projection model to find the top 23 and under NBA prospects.

The projections are built around my player projection model, the same one I use to project season win totals during the offseason. The played model I developed compares a slightly modified and regressed version of what a player has done over their previous three seasons to a database of historical season. For rookies, the model regresses current season performance to how the player projected out of college or overseas. The model finds similar players statistically/stylistically and uses how those players’ games changed as they aged as a crutch to augment a generic aging curve to better tailor it to the specific player’s style of play and skill set.

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A disclaimer before getting any further: the model is attempting to project events that are four to nine years from now depending on the player. The expected error on these is, rightly, pretty large. The younger a player is, the more error in the model. A rookie being ranked better or worse than you personally think is not an indictment on the player.

The way I decided to rank under-23 prospects was by projected Wins Added from age 26 to 28, generally a player’s three most prolific seasons. Wins Added is my cumulative impact statistic, comparable to RPM wins or VORP. For reference, the average starter provides about 5.0 Wins Added in value each season.


There are seven columns on the charts below and here is what they all mean:

  • Rank – Where the player ranked by peak Wins Added
  • Player – The player’s name
  • Age – Player’s age as of today, I used the Basketball-Reference method for what age season this is for a player
  • Peak %ile – Where the player’s projected 3-years Wins Added peak ranks among all players in my database (going back to 1973-74)
  • Wins Added – The numbers of wins a player is projected to add during their age 26 to 28 seasons
  • Minutes – A player’s projected minutes during their age 26 to 28 seasons
  • WA/48 – Wins Added per 48 minutes played, a conversion of Wins Added to a per minute rate to compare players with different minutes projections

To help you read WA/48, keep in mind that an average player provides 0.500 WA/48 and a replacement level player provides 0.426 WA/48.

A link to the entire list along with notes on each player’s projection and what the model might be seeing or missing is available at the bottom of the page.

Without further ado, let’s get to the list!

23-and-under prospects: 41 to 50

The most surprising part of this group was seeing Juan Hernangomez, Domantas Sabonis, and Julius Randle come in this low. Each projects to provide above average production on a per minute rate, but their low minutes projections pull them down to the bottom of the list. Randle getting out off the Lakers would drastically improve his ranking. Hernangomez continues to be played next to no minutes on the Nuggets. Sabonis is certainly playing more for the Pacers so I expect his projection to rise as the year goes on.

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