*Featured Image By Michael Hickey / Getty Images*

The NBA revolves around shooting these days, so it is crucially important for draft prospects to be able to shoot. We have seen countless talented prospects (Michael Kidd-Gilchrist, Justise Winslow, etc.) falter over the years in the NBA due to a lack of a reliable jump shot.

But it is hard to predict how shooting will translate from college to the NBA. The college three-point line is shorter, for one. For another, the seasons are shorter and amateur teams often play far less open offensive styles, so most players have not taken a high volume of attempts.

One good way to evaluate shooting is to use a statistical technique called Empirical Bayesian probability (see **here** for a good explanation). Using this technique, we regress a shooter’s three-point percentage towards the NCAA average three-point percentage, weighted by how many attempts the shooter had.

What Empirical Bayesian probability does is regress all players’ three-point percentage towards the NCAA average, but with a stronger regression for players with fewer attempts. The effect is shown in the graph below, with three-point percentage plotted on the x-axis against Empirical Bayesian three-point percentage (lighter dots represent shooters with less attempts):

The basic idea is that, if you have gone 6-for-10 on three-point attempts, you are probably not a 60 percent shooter (so we regress you heavily towards the average), but you probably are better than someone who is a 20-for-100 shooter (we are more confident they are a bad shooter since they have taken a large number of attempts).

A college player’s Empirical Bayesian three-point percentage has a slightly stronger relationship with NBA three-point percentage (0.13 R^2) than his raw college three-point percentage does (0.11 R^2), as shown below:

The leaders in Empirical Bayesian three-point percentage among this year’s college class are as follows:

Name | School | 3PA | 3P | Empirical Bayes 3P percent |

Aaron Nesmith | Vanderbilt | 115 | 60 | 40.2 percent |

Saddiq Bey | Villanova | 175 | 79 | 38.9 percent |

Desmond Bane | TCU | 198 | 87 | 38.7 percent |

Markus Howard | Marquette | 294 | 121 | 38.1 percent |

Cassius Winston | Michigan St. | 169 | 73 | 38.0 percent |

Using this statistic, I created a regression model for NBA three-point percentage based on Empirical Bayesian College three-point percentage, Empirical Bayesian College free-throw percentage, Empirical Bayesian shooting percentage on long twos (which includes basically all two point jump shots), Empirical Bayesian College three-point rate (the percentage of field goal attempts that were threes), and position. All statistics were taken from the player’s last season in college. Only players who had taken at least 100 threes in the NBA were included in the training set. I used data from **Bart Torvik’s site**, which is a great resource for college stats.

The R-squared value for the model is .155, meaning the model explains 15.5 percent of the variance in NBA three-point shooting percentage in the test set. The mean absolute error (MAE) of the model is .028. Since the model is predicting percentages, that means it was off by about 2.8 percent on the average player. The model has a root mean squared error (RMSE) of .039 on the test set. These error numbers are decent, since no one can predict shooting percentage with absolute certainty, but could stand to improve.

The model is very conservative. It never predicts a player to have an NBA three-point percentage above 40 percent, and only rarely predicts shooters to be below 30 percent. The best prediction in the training dataset came for Tyler Herro, who was predicted to shoot 38.4 percent from three in the NBA (he has slightly surpassed that, shooting 38.9 percent in his career). Luke Babbitt (38.3 percent), Ian Clark (38.2 percent), Luke Kennard (38.0 percent), and Bryn Forbes (38.0 percent) all also had high projections. On the other hand, Andre Drummond (27.4 percent) had the lowest projection in the set.

There have been some misses. Seth Curry (projected 37.2 percent, actual 44.3 percent), Duncan Robinson (projected 37.9 percent, actual 43.7 percent), and Michael Porter Jr. (projected 32.2 percent, actual 42.2 percent) have all shot far better than projected, especially Porter. Porter only played three regular season games in college, shooting 30 percent from three in those games, so his low projection is explainable, and a good reminder that scouting is very important. Relying solely on his statistics did not come close to telling the full story. As for Curry and Robinson, they are two of the best shooters alive, and are outliers that are hard to predict.

Of this year’s college draft prospects, The model predicts Kentucky guard Immanuel Quickley as the best shooter, with a projected NBA three-point field goal percentage of 38.2 percent. Sam Merrill (38.0 percent), Isaiah Joe (37.8 percent), and Markus Howard (37.3 percent) all also profile well. Meanwhile, Precious Achiuwa (29.0 percent), Lamine Diane (30.5 percent), Xavier Tillman (30.8 percent), and Isaac Okoro (30.9 percent) do not project well.

Among top prospects, Anthony Edwards (33.2 percent) does not project well due to a poor college three-point shooting percentage. James Wiseman (31.3 percent) and Onyeka Okongwu (31.8 percent) also do not project well, but they are big men, so that is more acceptable for them.

Below, see a table of NBA prospects shooting projections, including an 95 percent confidence interval (there is a 95 percent chance they will shoot in that range in the NBA).

Name | Predicted NBA 3P percent | CBS Sports Draft Ranking |

Immanuel Quickley | 38.2 percent | 52 |

Sam Merrill | 38.0 percent | 51 |

Isaiah Joe | 37.8 percent | 19 |

Markus Howard | 37.3 percent | 50 |

Ty-Shon Alexander | 37.0 percent | 67 |

Aaron Nesmith | 36.7 percent | 13 |

Nate Darling | 36.6 percent | 90 |

Cassius Winston | 36.6 percent | 39 |

Malachi Flynn | 36.3 percent | 45 |

Tyrell Terry | 36.3 percent | 20 |

Skylar Mays | 36.2 percent | 49 |

Payton Pritchard | 35.7 percent | 47 |

Tyrese Haliburton | 35.7 percent | 3 |

Elijah Hughes | 35.7 percent | 40 |

Jordan Nwora | 35.6 percent | 37 |

Malik Fitts | 35.2 percent | 60 |

Jalen Harris | 35.2 percent | 55 |

Saddiq Bey | 34.9 percent | 16 |

Grant Riller | 34.8 percent | 24 |

Nico Mannion | 34.6 percent | 33 |

Desmond Bane | 34.5 percent | 23 |

Killian Tillie | 34.5 percent | 53 |

Mason Jones | 34.4 percent | 56 |

Devin Vassell | 34.3 percent | 14 |

Kira Lewis Jr. | 34.1 percent | 10 |

Jaden McDaniels | 34.0 percent | 32 |

Tyrese Maxey | 33.9 percent | 11 |

Patrick Williams | 33.8 percent | 9 |

Jalen Harris | 33.6 percent | 55 |

Tre Jones | 33.6 percent | 34 |

Cole Anthony | 33.2 percent | 18 |

Anthony Edwards | 33.2 percent | 5 |

Obi Toppin | 33.1 percent | 7 |

Cassius Stanley | 33.1 percent | 27 |

Jahmi’us Ramsey | 33.1 percent | 36 |

Devon Dotson | 33.0 percent | 35 |

Zeke Nnaji | 33.0 percent | 43 |

Jalen Smith | 33.0 percent | 28 |

Isaiah Stewart | 33.0 percent | 31 |

Reggie Perry | 32.8 percent | 58 |

Tyler Bey | 32.8 percent | 42 |

Saben Lee | 32.8 percent | 59 |

Paul Reed | 32.7 percent | 44 |

Josh Green | 32.7 percent | 25 |

Ashton Hagans | 32.5 percent | 46 |

Daniel Oturu | 32.2 percent | 41 |

Robert Woodard II | 32.2 percent | 29 |

Onyeka Okongwu | 31.8 percent | 6 |

James Wiseman | 31.3 percent | 4 |

Vernon Carey Jr. | 31.3 percent | 38 |

Isaac Okoro | 30.9 percent | 15 |

Xavier Tillman | 30.8 percent | 26 |

Lamine Diane | 30.5 percent | 48 |

Precious Achiuwa | 29.0 percent | 17 |

*A previous version of the above table had a column with incorrect ranges. This column has been removed.*

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