All posts by Marc Richards

NHL Draft Model Results 2018 (Preliminary)

Below is results to our (preliminary) NHL Draft Model that uses prospects’ statistical production, physical measurements, and other variables to predict the likelihood that a players assume a specific NHL Role (i.e., First Line / Top Pair, Second / Third Line / 2nd pair defensemen, Fourth Line / Bottom pair defensemen, and Non-NHL player). The model is still being fine-tuned, hence the preliminary results, and an in-depth methodology article will come in the future. In addition to the aforementioned role probabilities, there is also a predicted NHL point per game that is derived from our Hockey Translation Factors.

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NBA 2018 Draft Prospect Sentiment Analysis

A couple months ago, we put together a My Model Monday series article that did a text and sentimental analysis of NBA Draft Prospects based on scouting reports. For those that are unaware, sentiment is “the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc., is positive, negative, or neutral.” Using Bing Liu’s graded sentiment dictionary, we can analyze text to and identify who is more positively written about. For more information, please read our My Model Monday series article.

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Prospect Profile: Lonnie Walker IV

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 Lonnie Walker IV.

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Model 284 Podcast: NBA Draft Models Big Board

With the NBA Draft less than a week, Sam and Marc go through ESPN / DX Express’s top 10 NBA Draft Prospects and what our Models are saying about them. Also, Sam and Marc give their top 10 ranked prospects combining all aspects of our Draft Models and other considerations not directly captured by the Models.

Prospect Profile: Deandre Ayton

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 Deandre Ayton.

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Prospect Profile: Wendell Carter Jr.

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.

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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.
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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.

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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.