I'm going to this (since I'm living in the Bay Area now), thought I'd post the announcement.
http://analytics.theiegroup.com/sports
Kirk Lacob giving a talk:
The Golden State Warriors Silicon Valley Startup: A New Era
Perspective on Technology & Data Analysis
Ben Alamar (OKC):
Treating Analytics as Innovation - Getting Good Tools Used
Kirk Goldsberry:
Visual Analytics for the NBA
Also looking forward to a football talk from Keith Goldner who does some cool Markov models:
Situational Analysis in the NFL & Fantasy Analytics
Sports Analytics Summit in San Francisco (Sept 20-21)
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
I'd be interested in hearing your report on the NBA topics after the fact.
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
By Twitter, of course.Crow wrote:I'd be interested in hearing your report on the NBA topics after the fact.

Re: Sports Analytics Summit in San Francisco (Sept 20-21)
If you want to post 300 tweets, that is fine. I'll read that.
By the way, when does your new metric get unveiled? Any blending involved?
I hope when you met one or both of the Lacobs they indicate they have read your stuff.
By the way, when does your new metric get unveiled? Any blending involved?
I hope when you met one or both of the Lacobs they indicate they have read your stuff.
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
I'll tell you what I did, but I want to work on it more before I post anything. The weights for A4PM were originally based on a regression on RAPM. I wanted to see what would happen if added interaction terms to the regression. So, for example, OREB*ORR*OFTR, etc. The rankings that currently are in the lead on my site ("C" - 89% of the vote currently) are the ones done with those interaction terms included. "A" is RAPM (mine, not Jerry's). "B" is A4PM without the interaction terms.Crow wrote:
By the way, when does your new metric get unveiled? Any blending involved?
Before I write more about it, though, I'd like to do more validation. Specifically, I want to calculate the predictive errors of each system. Adding all those interaction terms might give a better fit to the data, but may result in overfitting and worse prediction. (And I would be the first to admit that people may not like the idea of adding those terms, because the model becomes more of a black box.)
Hoping to get something done by the end of September, though.
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
Thanks for the explanation.
Would you have any interest in blending those 3 as another mark? From a technical perspective what would be the pluses and minuses of doing so? Could machine learning or some other technique be used to fine-tune the mix? Is the analogy of a multi-element lens applicable and useful or not?
Would you have any interest in blending those 3 as another mark? From a technical perspective what would be the pluses and minuses of doing so? Could machine learning or some other technique be used to fine-tune the mix? Is the analogy of a multi-element lens applicable and useful or not?
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
Awesome, an analytics conference in SF. But damn is that registration price steep. Evan, any chance you want to meet in person after the conference?
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
For sure, send me a pm and some contact info. You live in the Bay Area?
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
Evan, sent you a PM! I'll be lurking around on Thursday.
Re: Sports Analytics Summit in San Francisco (Sept 20-21)
The non-twitter update.
http://www.goldenstateofmind.com/2012/9 ... ion-summit
Would have taken 51 tweets.
Doesn't sound like it was that thrilling.
http://www.goldenstateofmind.com/2012/9 ... ion-summit
Would have taken 51 tweets.
Doesn't sound like it was that thrilling.