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Basketball Chicago Bulls Mathematics NBA NBA Finals NBA Playoffs Physics Science

Basketball – A Game of Geometry

In a previous post, I described the most optimal offensive strategy for the Knicks based on developing relevant joint probability density functions. In this post, I attempt a solution to the following problem: Given 5 players on the court, how can one determine (x,y) coordinates for each player such that the spacing / distance between each […]

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Basketball Data Analytics Data Science Mathematics NBA NBA Finals NBA Playoffs Sports Statistics

The Most Optimal Strategy for the Knicks

In a previous article, I showed how one could use data in combination with advanced probability techniques to determine the optimal shot / court positions for LeBron James. I decided to use this algorithm on the Knicks’ starting 5, and obtained the following joint probability density contour plots: One sees that the Knicks offensive strategy […]

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Basketball Data Analytics Data Science Mathematics NBA NBA Finals NBA Playoffs NCAA Statistics

Analyzing Lebron James’ Offensive Play

Where is Lebron James most effective on the court? Based on 2015-2016 data, we obtained from NBA.com the following data which tracks Lebron’s FG% based on defender distance: From Basketball-Reference.com, we then obtained data of Lebron’s FG% based on his shot distance from the basket: Based on this data, we generated tens of thousands of […]

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Basketball Chicago Bulls Data Analytics Data Science Mathematics NBA NBA Finals NBA Playoffs Science Sports Statistics Toronto

Breaking Down the 2015-2016 NBA Season

In this article, I will use Data Science / Machine Learning methodologies to break down the real factors separating the playoff from non-playoff teams. In particular, I used the data from Basketball-Reference.com to associate 44 predictor variables which each team: “FG” “FGA” “FG.” “X3P” “X3PA” “X3P.” “X2P” “X2PA” “X2P.” “FT” “FTA” “FT.” “ORB” “DRB” “TRB” […]

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Basketball Chicago Bulls Data Analytics Data Science Mathematics NBA NBA Finals NBA Playoffs NCAA Sports Statistics

Optimal Positions for NBA Players

I was thinking about how one can use the NBA’s new SportVU system to figure out optimal positions for players on the court. One of the interesting things about the SportVU system is that it tracks player coordinates on the court. Presumably, it also keeps track of whether or not a player located at makes […]

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Basketball Data Analytics Data Science NBA NBA Finals NBA Playoffs Sports Statistics

Basketball Paper Update

Everyone by now knows about this paper I wrote a few months ago: http://arxiv.org/abs/1604.05266 Using data science / machine learning methodologies, it basically showed that the most important factors in characterizing a team’s playoff eligibility are the opponent field goal percentage and the opponent points per game. This seems to suggest that defensive factors as […]

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Basketball Mathematics NBA NBA Finals Physics Science

The Mathematics of The Triangle Offense, Continued…

In a previous post, I showed how given random positions of 5 players on the court that they could “fill” the triangle. The main geometric constraint is that 5 players can form 3 triangles on the court, and that due to spacing requirements, these triangles are “optimal” if they are equilateral triangles. Given that we […]

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Basketball Data Analytics Data Science Mathematics NBA NBA Finals Sports Statistics

What are the factors behind Golden State’s and Cleveland’s Wins in The NBA Finals

As I write this, Cleveland just won the series 4-3. What was behind each team’s wins and losses in this series? First, Golden State: A correlation plot of their per game predictor variables versus the binary win/loss outcome is as follows:  The key information is in the last column of this matrix:  Evidently, the most […]

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Basketball Mathematics NBA NBA Finals NBA Playoffs Physics Science

The Mathematics of “Filling the Triangle”

I’ve been fascinated by the triangle offense for a long time. I think it is a beautiful way to play basketball, and the right way to play basketball, in the half-court, a “system-based” way to play. For those of you that are interested, I highly recommend Tex Winter’s classic book on the topic. There is […]

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Basketball Data Analytics Data Science NBA NBA Finals Sports Statistics

Game 2 of CLE vs GSW Breakdown

As usual, here is the post-game breakdown of Game 2 of the NBA Finals between Cleveland and Golden State. Using my live-tracking app to track the relevant factors (as explained in previous posts) here are the live-captured time series: Computing the correlations between each time series above and the Golden State Warriors point difference, we […]