Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at Wendell Carter Jr.
Category Archives: NBA Draft
Prospect Profile: Shai Gilgeous-Alexander
Leading up to the 2018 NBA Draft on June 21st, we will be using our NBA Draft Models (PNSP Model, Role Probability Model, and Similarity Scores) to investigate this year’s top prospects. These Prospect Profiles look at which stats affect NBA projections, present unique data points from a player’s stats, and give relevant comparisons to current NBA players. You can find all of our Prospect Profiles here or through the header menu above (NBA –> NBA Draft –> Prospect Profiles). In today’s article, we look at yet another Kentucky freshman, Shai Gilgeous-Alexander.
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2018 Similarity Score Tool
Select any 2018 NBA Draft prospect from the drop-down menu below to view their top 10 most similar college basketball players. Similarity Scores provide insight into how a player will translate to the NBA based on how their historical comparisons have performed in the NBA. This model considers a player’s college production, physical measurements, and age/experience to generate their most similar historical players. For more background on the calculation of the similarity scores, see this article. This model is one of three pieces that we use to evaluate the NBA potential of college players, with the other two being PNSP and NBA Role Probability Model.
Continue reading 2018 Similarity Score Tool
2018 NBA Role Probability Model
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 2018 prospect landing in a given role in the NBA.
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2018 Peak NBA Statline Projection Model
Peak NBA Statline Projection (PNSP) is a model used to project NBA success for college and International basketball players. PNSP considers each player’s individual and team statistics, physical measurements, high school scouting ranking, and age/experience. The PNSP model returns a single rating value from 0 to 100, with higher values indicating a “better” NBA prospect. We provide a detailed article outlining how PNSP is formulated here, and PNSP rankings from previous years can be found here. Below are a few highlights from PNSP’s ratings for the 2018 NBA Draft Class.
Model 284 Podcast: NBA Draft Models
On this episode of the Model 284 Podcast, Sam and Marc are joined by fellow Model 284er Jack Werner to give some background on our NBA Draft models, discuss draft theory and positional value, and look a bit at the 2018 draft class.
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My Model Monday: NBA Draft Scouting Text Analysis
With March Madness just wrapping up, the natural next step in the basketball calendar is to turn to the NBA Draft. At Model 284, we have created a number of different models projecting college basketball players in the NBA; these include: our Peak NBA Statline Projection (PNSP) which attempts to predict overall NBA ability on a scale of 0-100, Similarity Scores that capture style of play, and lastly, a Role Probability Model which puts a probability that each player ends up in a certain role in the NBA (All-Star, Starter/Sixth Man, Bench, or out of the league). One idea which has come up repeatedly in our draft analysis is incorporating scouting or subjective analysis into our draft models. Rather than using a rubric of someone’s scouting grades, I wanted to do a text analysis of scouting reports already written. Since DraftExpress recently folded and moved to the dark side with ESPN Insider (probably a smart business decision), I used NBADraft.net. Continue reading My Model Monday: NBA Draft Scouting Text Analysis
Prospect Profile: Justin Patton
Leading up to the 2017 NBA Draft, we will be diving into what our Draft Models tell us about this year’s top prospects. Our NBA Draft Models include the PNSP Model, NBA Role Probability Model, and Similarity Scores which each provide unique ways of evaluating college prospects. Our Prospect Profiles look at which stats positively/negatively affect NBA projections, unique data points from a player’s stats, and relevant comparisons to current NBA players. You can find links to all of our Prospect Profiles in the header menu above (NBA –> NBA Draft –> Prospect Profiles). In this article, we look at Minnesota Timberwolves selection Justin Patton.
Prospect Profile: Lauri Markkanen
Leading up to the 2017 NBA Draft, we will be diving into what our Draft Models tell us about this year’s top prospects. Our NBA Draft Models include the PNSP Model, NBA Role Probability Model, and Similarity Scores which each provide unique ways of evaluating college prospects. Our Prospect Profiles look at which stats positively/negatively affect NBA projections, unique data points from a player’s stats, and relevant comparisons to current NBA players. You can find links to all of our Prospect Profiles in the header menu above (NBA –> NBA Draft –> Prospect Profiles). In this article, we look at Finnish-born Arizona product Lauri Markkanen.
Model 284 NBA Draft Board
Using a combination of our NBA Draft Models (PNSP, NBA Role Probabilities, & Similarity Scores), we have created a consensus ranking for the 2017 NBA Draft. For example, Jawun Evans ranks 40th by PNSP but has the 7th highest All-Start probability in the class, so we have him ranked higher than 40th on our draft board. These rankings are meant to take into account the predictions from all of our models, while also considering any outside factors that the models do not directly account for (e.g., off-court issues, NBA fit, ranking within a position, model biases, etc.). It should also be noted that international prospects are not included in our models or our draft board.