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About Me

I’m a college freshman and lifelong Celtics fan. I’ve been interested in statistics for a long time, and am starting Dribble Analytics to explore my interest in basketball analytics while learning Python and data science. To read more about the blog and my story, check out the “About” page.

Contact me at: the name of this blog [at] gmail [dot] com

Category: Regression

January 3, 2020January 3, 2020

Using machine learning to find the best and worst value contracts

Let’s evaluate contracts in the NBA by applying machine learning to compare how much a player earns versus how much the models expect them to earn.

Posted in Regression. Leave a comment
June 20, 2019June 20, 2019

Predicting the best scorers in the 2019 draft with machine learning

With the 2019 draft unclear looking inconsistent after the top 3, let’s try to predict the best scorers in the draft with machine learning. Who will be the hidden gem who could shine as a scorer?

Posted in Regression, The Draft. Leave a comment
April 12, 2019April 11, 2019

Using machine learning to predict the 2019 MVP and All-NBA teams: end of season predictions

Over the past few months, we’ve been using machine learning to predict the MVP and All-NBA teams. Now that the season is done, let’s update these predictions and predict our final MVP and All-NBA teams.

Posted in Classification, NBA Awards, Regression. Leave a comment
February 19, 2019June 17, 2019

Using machine learning to predict the 2019 MVP: All-Star break predictions

This is the second installment of predicting the 2019 MVP with machine learning. Since the first installment, James Harden has strengthened his MVP case, while Giannis Antetokounmpo has continued to lead the NBA-leading Bucks. Meanwhile, Paul George’s hot streak has shaken up the rest of the pack.

Posted in NBA Awards, Regression. Leave a comment
January 16, 2019June 17, 2019

Using machine learning to predict the 2019 MVP: mid-season predictions

With the halfway point in the year passing, the MVP discussion is heating up. James Harden and Giannis Antetokounmpo find themselves in a tight 2-man race for MVP. Let’s see who should win based off historical precedent for MVP vote share.

Posted in NBA Awards, Regression. Leave a comment
August 2, 2018June 17, 2019

Finding the least and most deserving MVPs of the last decade

Every few years, there’s a highly controversial MVP pick. Most recently, Russell Westbrook won MVP over James Harden on the back of a historic season where he average a triple-double. Let’s look at the historical precedent for MVP vote share and determine the least and most deserving MVPs.

Posted in NBA Awards, Regression. Leave a comment
July 16, 2018June 17, 2019

Using machine learning to predict the best distributors in the 2018 draft

Though the top of the 2018 draft seems heavy on bigs and forwards, there’s bound to be several starting guards coming out of the draft class. Let’s see who has the best distributing ability by using historical college stats to predict NBA assists and turnovers.

Posted in Regression, The Draft. Leave a comment
June 21, 2018June 17, 2019

Using machine learning to predict the best defenders in the 2018 draft

With defensive freaks like Mohamed Bamba and Jaren Jackson Jr., this draft class seems strong defensively. Examining how historical players’ college stats predicted their NBA defense, we can predict the best defenders for this upcoming draft class.

Posted in Regression, The Draft. 2 Comments
June 1, 2018June 17, 2019

Using machine learning to predict the top shooters in the 2018 draft

With the NBA’s modern emphasis on 3-point shooting, draft good shooters has become more and more important. By looking at how historical players’ college shooting stats predicted their NBA PPG, we can predict the best shooters in the upcoming draft class.

Posted in Regression, The Draft. 1 Comment
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