The NBA Role Probability Model predicts the likelihood that a given college basketball player becomes an All-Star, starter, bench player, or does not make it in the NBA. The model considers individual box score statistics, team-level statistics (e.g. strength of schedule), physical measurements, high school scouting rank, position, and age/experience to predict the probability of a player landing each NBA role. For more detail on how this model is formulated, see this article. The Role Probability model is one of three pieces that we use to evaluate the NBA potential of college and international players, with the other two being PNSP and Similarity Scores. In the table below, you can find the model’s predicted probabilities for each 2019 prospect landing in a given role in the NBA.
Highlights
Just as he did with PNSP, Zion Williamson ranks number one in All-Star Probability at 75%. It probably does not take an analytical model to tell you that Zion should be the number one pick (barring any unforeseen circumstances), but I suppose that’s what we are doing here. Recent players with modeled All-Star probabilities above 70% include Luka Doncic, Kevin Durant, Michael Beasley, Lonzo Ball, Ben Simmons, Joel Embiid, and DeMarcus Cousins. I think it’s safe to say that scouts and analytics agree here.
Next, Ja Morant‘s shows up in the model as a high risk, high reward player with a 50/50 chance of becoming an All-Star and nearly 20% chance of not making the NBA. The high “bust-ability” is driven by playing for a mid-major program at Murray State and not being heavily recruited out of high school. Even given this decent likelihood of not becoming an NBA player, our Role Probability Model agrees with PNSP that Ja Morant is the clear cut #2 prospect in this year’s draft.
PNSP’s number 3 ranked prospect Brandon Clarke doesn’t appear as appetizing at first glance, with only a 6% All-Star Probability. However, he ranks number 1 in starter probability at 60% and top 10 in making the NBA (1 – non-NBA probability). This suggests that Brandon Clarke should be a productive NBA player but likely won’t be a franchise-altering one. In a similar vein, Auburn’s versatile forward Chuma Okeke shows up strongly again with a high probability of making the NBA (87%). Okeke shot roughly 40% from 3, with STL% and BLK% of 3.6% and 5.5%, respectively, while contributing on the boards.
On the flip side, the behemoth Tacko Fall lands the highest bust-ability at 65%. Given Tacko’s freakish length and 35% Free Throw shooting, it shouldn’t come as a surprise that he has a decent chance of never making any noise in the NBA. Iowa Big man Tyler Cook also shows up with > 50% bust-ability.
Stay tuned for the release of our 2019 Similarity Scores and other draft coverage leading up to June’s NBA Draft. And as always #TrustTheModel
| PLAYER | POS | ALL-STAR | STARTER | BENCH | NON-NBA |
|---|---|---|---|---|---|
| Zion Williamson | PF | 74% | 22% | 3% | 1% |
| Ja Morant | PG | 52% | 14% | 17% | 17% |
| Bol Bol | C | 31% | 43% | 17% | 9% |
| RJ Barrett | SG/SF | 30% | 43% | 19% | 8% |
| Jontay Porter | C | 22% | 40% | 27% | 10% |
| Nassir Little | SF/PF | 20% | 38% | 22% | 20% |
| Nickeil Alexander-Walker | SG | 19% | 29% | 31% | 22% |
| Jarrett Culver | SG/SF | 18% | 41% | 28% | 13% |
| Talen Horton-Tucker | PG/SG | 17% | 18% | 14% | 51% |
| P.J. Washington | PF/C | 15% | 36% | 43% | 7% |
| Luguentz Dort | PG/SG | 14% | 16% | 28% | 42% |
| Chuma Okeke | PF | 12% | 43% | 33% | 13% |
| Goga Bitadze | C | 11% | 25% | 52% | 12% |
| Romeo Langford | SG/SF | 11% | 45% | 29% | 15% |
| Daniel Gafford | PF/C | 11% | 34% | 31% | 25% |
| Nicolas Claxton | PF/C | 10% | 21% | 45% | 24% |
| Rui Hachimura | PF/C | 10% | 45% | 24% | 21% |
| Coby White | PG/SG | 10% | 32% | 32% | 27% |
| Dylan Windler | SF/PF | 10% | 49% | 24% | 18% |
| Carsen Edwards | PG | 10% | 26% | 44% | 21% |
| De'Andre Hunter | SF/PF | 10% | 15% | 54% | 22% |
| Grant Williams | PF | 9% | 41% | 33% | 18% |
| KZ Okpala | SF | 9% | 11% | 41% | 40% |
| Cameron Reddish | SF/PF | 8% | 41% | 38% | 13% |
| Mfiondu Kabengele | PF/C | 8% | 15% | 54% | 23% |
| Naz Reid | PF/C | 8% | 25% | 37% | 30% |
| Simisola Shittu | PF/C | 8% | 37% | 37% | 18% |
| Reggie Perry | SF/PF | 7% | 25% | 24% | 44% |
| Bruno Fernando | C | 7% | 39% | 30% | 24% |
| Jalen McDaniels | SF/PF | 7% | 32% | 23% | 38% |
| Miye Oni | SG/SF | 7% | 18% | 32% | 44% |
| Moses Brown | C | 6% | 32% | 16% | 45% |
| Zach Norvell Jr. | SG | 6% | 38% | 34% | 23% |
| Tremont Waters | PG | 6% | 44% | 27% | 23% |
| Brandon Clarke | PF | 6% | 60% | 22% | 13% |
| Kevin Porter Jr. | SG/SF | 6% | 20% | 32% | 42% |
| Jaxson Hayes | C | 5% | 52% | 27% | 16% |
| Matisse Thybulle | PG/SG | 5% | 42% | 33% | 19% |
| Keldon Johnson | SG/SF | 5% | 21% | 36% | 38% |
| Darius Garland | PG/SG | 5% | 40% | 34% | 21% |
| Shamorie Ponds | PG/SG | 5% | 46% | 27% | 23% |
| Sekou Doumbouya | SF/PF | 5% | 41% | 33% | 21% |
| Cody Martin | PG/SG | 5% | 41% | 22% | 33% |
| Tacko Fall | C | 5% | 10% | 19% | 65% |
| Ky Bowman | PG | 5% | 18% | 21% | 56% |
| Dedric Lawson | PF/C | 5% | 33% | 27% | 35% |
| Quinndary Weatherspoon | SG/SF | 5% | 30% | 41% | 24% |
| Devon Dotson | PG | 5% | 35% | 33% | 29% |
| Terence Davis | SG | 5% | 24% | 24% | 48% |
| Ignas Brazdeikis | SF | 4% | 20% | 45% | 30% |
| DaQuan Jefferies | SF/PF | 4% | 29% | 38% | 30% |
| Tyler Herro | PG/SG | 4% | 35% | 28% | 33% |
| Jaylen Hands | PG | 4% | 25% | 30% | 41% |
| Jordan Nwora | PF | 4% | 24% | 45% | 27% |
| Jaylen Nowell | SG | 3% | 31% | 43% | 23% |
| Jalen Hoard | PF/C | 3% | 23% | 37% | 37% |
| Oshea Brissett | SF/PF | 3% | 11% | 29% | 57% |
| Killian Tillie | PF/C | 3% | 39% | 38% | 21% |
| Jared Harper | PG | 3% | 18% | 46% | 33% |
| Louis King | SF/PF | 3% | 24% | 32% | 41% |
| Amir Coffey | SG/SF | 2% | 21% | 46% | 31% |
| Quentin Grimes | SG | 2% | 15% | 51% | 32% |
| Isaiah Roby | PF/C | 2% | 18% | 44% | 37% |
| Dewan Hernandez | C | 2% | 16% | 43% | 39% |
| Tyler Cook | PF/C | 2% | 12% | 30% | 56% |
| Ty Jerome | PG/SG | 2% | 16% | 32% | 51% |
| Eric Paschall | SF/PF | 2% | 6% | 41% | 51% |
| Luka Samanic | SF/PF | 2% | 19% | 42% | 38% |
| Admiral Schofield | SG/SF | 2% | 6% | 32% | 61% |
| Yovel Zoosman | SF | 2% | 14% | 50% | 35% |
| Marial Shayok | SF/PF | 2% | 16% | 44% | 38% |
| Kris Wilkes | SF/PF | 2% | 12% | 47% | 40% |
| Jordan Bone | PG/SG | 2% | 17% | 44% | 38% |
| Kyle Guy | PG/SG | 2% | 14% | 39% | 45% |
| Terance Mann | SG/SF | 2% | 11% | 38% | 50% |
| Didi Louzada Silva | SG | 1% | 6% | 45% | 48% |
| Jordan Poole | SG/SF | 1% | 16% | 52% | 31% |
| Deividas Sirvydas | SF/PF | 1% | 12% | 50% | 37% |
| Cameron Johnson | SG/SF | 0% | 32% | 49% | 19% |
*Data retrieved from Basketball Reference, Sports Reference, and DraftExpress.
Written by Marc Richards and Jack Werner.
49 thoughts on “2019 NBA Role Probability Model”
Comments are closed.