The NBA Draft Contains Multiple College Players That Should Have Immediate Impact

The first round of the NBA draft occurs tonight (June 26th) with a dominant story line being that this is a “down” year without top-end draft prospects.

?The model I have created to help predict future on-court NBA performance for current college players provides evidence both against and supporting this claim.

?As context, I developed the Revenue Above Replacement model to determine a player’s value to his team based on his on-court and off-court performance. I only examined college players in this analysis given that the datasets available make comparisons with ?non-college players (particularly international players) difficult to analyze.

?To determine on-court performance, I examined hundreds of players across multiple NBA seasons to identify the factors that are most strongly correlated with NBA teams winning games. The result of this model is to calculate the number of “NBA Wins” each player contributes to his team for each season.

?I then built a separate predicative model to determine how current NCAA performance is associated with future NBA Wins (i.e., how does a college player’s 2022-23 college season correlate with his projected 2023-24 NBA season). I identified multiple factors that provided a strong correlation to NBA Wins by analyzing the ?2020-21 through the 2022-23 NCAA basketball seasons.

The results of my analysis are in the table below for the 2024-25 NBA draft class with the primary findings highlighted in the green columns. “Projected NBA Wins” examines how a player’s current college season should correlate with his performance during his next (rookie) NBA season. The Percentile metric shows where each player ranks as compared to NCAA players in the previous three NBA draft classes.

I focused on college players that are frequently considered likely to be selected in the lottery level of the NBA draft (top 14 picks) or have received substantial media attention.

The analysis shows that multiple players are worthy of top-end draft grades given they are above the 84.5% percentile. For example, Donovan Clingan is a worthy top of the draft pick if he is selected given that he is the sixth highest rated player examined across the past four seasons.

?Some of the factors my model more heavily emphasizes are blocks, rebounds per minute played, and effective shooting (in this case a combination of total points and field goal percentage). Clingan performs well on all of these factors.

?Zach Edey, however, performs nearly as well or better than Clingan in these key metrics. In fact, Edey had the highest effective shooting of any player over the past four years. Edey committed more turnovers and personal fouls, which is why he is ranked lower than Clingan in “Projected NBA Wins.”

?My model does also indicate that the middle to lower end of the draft may not be as talented as it is likely to be in future years. Dalton Knecht is the eighth ranked college player in this analysis for this year’s draft.

?Knecht would have been the 20th ranked college player in the 2021 draft, the 18th ranked college player in the 2022 draft, and the 19th ranked college player in 2023 draft. That indicates that there is a decrease in potential impact of players later in this year’s draft compared with other years.

?There are numerous caveats for this analysis many of which will be similar refrains for any predicative models. The main caveat is that this model has a solid, but not perfect, correlation between NCAA and NBA performance.

?That means the model will not be perfectly (or close to perfectly) predicative of future performance or be the sole way to evaluate players. For example, Edey’s NCAA effective shooting may not continue at the NBA level and that would make him a less valuable player.

?However, the model does provide directional insights that should be useful when examining future on-court performance. In particular, it does indicate that there are multiple players that should have substantial impact on their NBA teams next season.