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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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Data Analytics Data Science Elections Mathematics Politics Statistics

2016 Real-Time Election Predictions

Further to my original post on using physics to predict the outcome of the 2016 US Presidential elections, I have now written a cloud-based app using the powerful Wolfram Cloud to pull the most recent polling data on the web from The HuffPost Pollster, which “tracks thousands of public polls to give you the latest […]

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Data Analytics Data Science Politics Statistics

Will Donald Trump’s Proposed Immigration Policies Curb Terrorism in The US?

In recent days, Donald Trump proposed yet another iteration of his immigration policy which is focused on “Keeping America Safe” as part of his plan to “Make America Great Again!”. In this latest iteration, in addition to suspending visas from countries with terrorist ties, he is also proposing introducing an ideological test for those entering […]

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Data Analytics Data Science Elections Finance Mathematics Politics Statistics Uncategorized

Some Thoughts on The US GDP

Here are some thoughts on the US GDP based on some data I’ve been looking at recently, mostly motivated by some Donald Trump supporters that have been criticizing President Obama’s record on the GDP and the economy.  First, analyzing the real GDP’s average growth per year, we obtain that (based on a least squares regression […]

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Data Analytics Data Science Gun Violence Mathematics Politics Statistics

Protected: Breaking Down The Data of Victims of Police Violence

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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 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 […]

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Basketball Data Analytics Data Science Mathematics NBA NBA Finals Statistics

Game 1 of CLE vs GSW Breakdown

Using my live tracking app combined with the relevant factors based on this previous work, here is my breakdown of what contributed to the Warriors win in Game 1 of the NBA Finals.  First, here is the time series graph of several predictor variables:  Breaking this down a bit further, we have:  Computing the correlations, […]

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

Breakdown of Game 7 between OKC and GSW

Here is the collection of time series of relevant predictor variables captured live during Game 7 of the Western Conference Finals between The Oklahoma City Thunder and The Golden State Warriors: Another video animation: https://twitter.com/dr_ikjyotsinghk/status/737694089437716480 Many commentators are making a point to mention how many three point shots The Warriors made, suggesting that that was […]

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

Metrics for GSW vs. OKC Game 6 Second Half

Continuing with the live metrics employed yesterday, here is an analysis of the second half of the Warriors-Thunder Game 6.  Here is a plot of the various time series of relevant statistical variables:  One can see from this plot for example, the exact point in time when OKC loses control of the game.  Further, here […]