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 […]

# Category: Statistics

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, […]

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 […]

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 […]

Yesterday for the first time, I took the playoff game between Cleveland and Toronto as an opportunity to test out a script I wrote in R that keeps track of key statistics during a game in real time (well, every 30 seconds). Based on previous work, it is evident that championship-calibre teams are the ones […]

I’ve been ranting a lot about the so-called “value” of the three-point shot in “modern-day” basketball. I know! But, here is yet one more entry. The common consensus is that teams are shooting more three point shots as discussed in the articles below: http://www.businessinsider.com/nba-three-point-shooting-2016-3 http://www.nba.com/2014/news/features/john_schuhmann/11/07/history-of-the-three-point-shot/ http://nyloncalculus.com/2016/03/08/three-pointers-and-skill-displacement/ There are several more where these have come from. […]

A few weeks ago, I published a paper that used data science / machine learning to detect commonalities between NBA playoff teams. I have now updated and extended it to detect commonalities between NBA championship teams using artificial neural networks, which is a field of deep learning. The paper can be accessed by clicking on the […]

A new and formal paper of mine describing how one can use machine learn methodologies to help determine which NBA teams will make the playoffs is now online: arXiv link SSRN link Have a look!

It is another New York Knicks season where fans have to wait until next year to see if the Knicks will make the playoffs or not. Yesterday, there was a lot buzz around the idea that Phil Jackson may want to keep Kurt Rambis on as head coach, and as usual, there were numerous people […]

As a long-time Golden State Warriors fan (go Tim Hardaway and Chris Mullin!), I have been watching the Warriors this season with great interest. Stephen Curry has been getting a lot of attention. It is somewhat of a foregone conclusion that he will be the MVP this season, but, I am not completely convinced, in […]