Category Archives: Basketball

My Model Monday: Predicting NBA Awards

  1. Now that the NBA season is halfway completed, I trained a model to predict the major individual award winners – MVP, Defensive Player of the Year, and Rookie of the Year, using statistics from the first half of the season. The modeled probabilities do not reflect who we at Model 284 think should win the award; instead, they indicate the probability of a given player winning the award based on the statistics from the players who the voters have chosen in the past.  Continue reading My Model Monday: Predicting NBA Awards

Freelance Friday: The NBA’s Forgotten Lefties

Being left-handed in the game of basketball, along with most other sports, doesn’t come with the same advantage that it does in the baseball world. At least in terms of strategy it doesn’t – but if you ask me, there are few things in this world as aesthetically pleasing as a fundamental left-handed jump shot, and I’m beyond certain CEO Marc would tell you the same thing. Perhaps I’m biased as someone that has a dominant left hand, but something about the quirkiness and funk of a lefty’s game is a thing of beauty, but unfortunately goes underappreciated by the average fan.
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My Model Monday: Crash the Glass or Get Back?

In the seconds immediately following a shot attempt, the players on offense can take one of two actions: (1) get back on defense to prevent a potential transition bucket from your opponents, or (2) crash the paint to get in position for an offensive rebound. In the article below, I explore the positive and negative impacts of each option. Continue reading My Model Monday: Crash the Glass or Get Back?

NBA Lineup Evaluator: Spacing (2016-2017)

Below is a table of our NBA Lineup spacing metric applied to all NBA Lineups that played more than 50 minutes together in the 2016-2017 season. Our NBA Lineup Spacing metric seeks to quantify a lineup’s ability to generate and score from efficient shots (i.e. at the rim and from the three point line). For complete methodology behind the calculation, see here.

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NBA Lineup Evaluator: Spacing

Preface

First and foremost, I regret to inform you that this analysis is NOT done with player tracking data.

Secondly, I want to say this lineup metric is called spacing, but it is not really a measure of spacing; it is more a measure of how capable a lineup is of producing efficient shots. So, why call it spacing? Firstly, because spacing is catchy and trendy, but also because we believe that when the average fan thinks or hears the word spacing, they are generally thinking about maximizing the optimal shots in basketball: three-pointers and shots at the rim.

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NBA Lineup Evaluator: Diversity

In most sports and at most skill levels, if you are unpredictable in your movements and actions you will have a better chance at being successful; you’ll have a better chance of beating your defender if he doesn’t know what you’re going to do. Granted, at the end of the day, high-performance level always wins out, but one can give themselves a better chance of winning a battle by being unpredictable or diverse.

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Components Methodology: NBA Lineup Evaluator

This article details the methodology and calculations of the components found on our NBA Lineup Evaluator. Each component represents a different skill or ability an NBA lineup could have. We can use these to asses strengths and weaknesses of NBA lineups that have yet to play together, or that haven’t played enough minutes to accurately evaluate their performance. Data is trained from NBA Lineups from 2015-2017 that played at least 50 minutes together. All data comes from either NBA.com or Basketball-Reference.com.

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