# That Other Site I Work On

This site has been sparse lately and it is because I’ve been busy with two other projects.

The first is my actual day job. I finished my PhD in May of 2017 and began working at Verily Life Sciences in August of 2017. Did I turn down some jobs with pro teams? Yes. Yes I did. Why? That’s a story for another day. I like what I do at Verily. I get to have fun, with people I like, working on cool healthcare projects. Plus we work out of the Google offices in Cambridge which are very nice and full of free food and fun toys.

The second project I’ve been working on is the visualizations section of Udam Saini’s EightThirtyFour.

http://eightthirtyfour.com/visualizations

Udam and I worked together on this site’s NBA foul project, which started as an attempt to quantify how mad DeMarcus Cousins gets in games. We built survival models and visualizations to examine how players accrue fouls. But these models can just as easily be applied to assists, blocks etc. In fact, I took the ideas and examined how Russell Westbrook accrued assists in his historic triple-double season. By using survival models, we can see how the time between assists increased significantly after he reached 10 assists in a game. This could be seen as evidence in favor of stat padding.

The tool we’ve built on the site linked above allows you to look at survival visualizations and models for pretty much any player in seasons between 2011 and 2017. The stats primer linked in the first line has more explanation and some suggestions for players and stats to look at.

Survival analysis models and visualizations are not always the easiest to explain, but I think there is value in having other ways to analyze and examine data. Survival analysis can help us better understand things like fatigue and stat padding. And can help add some math to intangible things like “tilt.”

This project was also a lesson in working on a problem with a proper software engineer. I am a statistician and I’m used to a certain amount of data wrangling and cleaning, but I largely prefer to get data in a nice data frame and go from there. And I certainly don’t have the prowess to create a cool interactive tool on a website that blends SQL and R and any number of other engineer-y things. Well. I’d like to think I could, but it would take ages and look much uglier. And be slower. Conversely, my partner in crime Udam probably can’t sort through all the statistics and R code as fast as I can. My background isn’t even in survival analysis, but I still understand it better than a SWE. So this part of his site was a chance for us to combine powers and see what we could come up with. In between our actual Alphabet jobs, of course.

I think in the world of sports analytics, it’s hard to find somebody who has it all: excellent software engineering skills, deep theoretical knowledge of statistics, and deep knowledge of the sport (be it basketball or another sport). People like that exist, to be sure, but they likely already work for teams or are in other fields. I once tried to be an expert in all three areas and it was very stressful and a lot of work. Once I realized that I couldn’t do it all by myself and started looking for collaborations, I found that I was able to really shine in my expert areas and have way more fun with the work I do.

The same is true in any field. I wasn’t hired by Verily to be a baller software engineer *and* an expert statistician *and* have a deep understanding of a specific health care area. I work with awesome healthcare experts and engineers and get to focus just on my area of expertise.

In both my job and my side sports projects my goal is always to have fun working on cool problems with people I like. It’s more fun to be part of a team.

Anyway, have fun playing with the site, and if you have any suggestions, let us know :]