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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: The Draft

July 26, 2019July 26, 2019

Using machine learning to predict All-Stars from the 2019 draft

Let’s use college stats to predict All-Star probabilities for the top-10 picks in the 2019 draft.

Posted in The Draft. Leave a comment
July 8, 2019July 18, 2019

Generating stats-based historical comparisons for the draft lottery

As soon as a player is drafted, we compare them to historical stars based on their play styles. Let’s use their stats and some similarity metrics to create more concrete comparisons.

Posted in Similarity, The Draft. 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
May 3, 2019May 2, 2019

A new approach to analyzing the value of tanking: Markov chains

Many claim tanking is worth it because players drafted earlier have a higher chance of being good. However, the draft is random. Let’s use Markov chains (a random process) to analyze if tanking is worth it.

Posted in The Draft. 2 Comments
October 2, 2018April 7, 2019

Using machine learning to predict hall of famers and all stars from the 2017 draft

Out of the first round in every draft class, on average, only 1 player makes the hall of fame, and about 2-3 players make an All-Star game at some point in their career. Let’s use classification models to see who those players are from the 2017 draft class.

Posted in Classification, The Draft. 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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