#SSAC16 wrap-up

Good afternoon!  DataGEEK here.

It’s been three weeks (or so my WordPress tells me, I can’t believe that it’s really been three weeks already) since my last post, which was in the middle of #SSAC16, the Sloan Sports Analytics Conference. Day Two of the conference was a blur, and very busy, so I never got a chance to write a recap of Day Two.

Day Two of #SSAC16 was more of the same of Day One, though I definitely felt less overwhelmed and more like I belonged at the conference. Meeting up with Bill Connelly of SBNation/Football Study Hall near the end of Day One made a big difference; Bill is one of my idols in sports analytics, and we’ve had a decent relationship on Twitter over the years, so meeting him in person went a long way toward making me comfortable.

Without further digression, some takeaways from #SSAC16 that I didn’t address in my Day One post:

Bill James: “Find the value in what can he do”

I admittedly don’t remember the full context of this quote/paraphrase from Bill James that I wrote down, in part because it came from the #MoneyballReunion panel that opened the conference. But from what I remember, the discussion was about how front-offices can focus too strongly on what a player can’t do. In fact, I remember Paul DePodesta mentioning during that panel that frequently a player that is already liked will be discussed in context of what he can do, while a similar player, but for whom the decision is that the scout or organization doesn’t like them, will be discussed in context of what he can’t do.

What you’ll frequently (read: hopefully, if I actually post frequently) on this blog is not just what I find or read about on the Internet, but also how that applies to my own self-centered worldview. This James quote is a perfect example, as you can apply it both to the workplace (new candidates can be written off on a simple first impression) but also as self-reflection. I find myself frequently judging myself for what I should have done, could have done, or can’t do.  Focusing on what I can do would certainly go a long way.

If you’re interested in analytics, take classes on R.

This is another one from Day One of the conference, but it was reinforced in spades on Day Two. Jessica Gelman, current VP with the Kraft Group and also one of the co-founders of #SSAC16, cited R as a hot trend in the analytics industry, and recommended people with an interest turn that way. That was very interesting for me, because I’ve kind of been assuming for months, if not years, that R was ubiquitous in data analytics. But more than once during the conference I heard people deride performing analytics in Excel. I guess more are still doing that than I thought?

Quick plug for anyone that reads this and has an interest in R: Baseball Hacks by Joseph Adler has a lot of tips for beginning in analytics, including tools and techniques. One of those tools is R, and the techniques in the book don’t just apply to baseball.

Start small and prove you can do something

At some later date I’m going to have a much longer post about this, but the biggest takeaway I had from the conference, especially with some of the career-focused panels I sat in on Day Two, was how critical, not just important but fundamentally critical, it is to actually do stuff.

Any job seeker, myself included, will find job postings for jobs that they have absolutely no experience with and the first thought is “I could do that”.  I actually went so far as to apply to one of those jobs, an Associate Athletics Director job at Saint Louis University, despite knowing that I didn’t have the exact right experience they were looking for (and sure enough, I got a nicely worded rejection letter saying as much). As I was reminded, the chances that some company will take a risk on you if you don’t have proven skills (unless you’re just out of school, entry-level, and low-cost) is frankly pretty low.

The solution is simple: Prove it.  As Nike would say: Just Do It. Or as Jacob Rosen put it: “Do shit.”

That’s why I’m here (on WordPress) and why I was in Boston for #SSAC16 in the first place. I wanted to see if I really wanted to get involved in analytics, and GEEKinSTL is going to be my outlet for that work. What I heard and read at #SSAC16 just reinforced my reason for being there, which was the best outcome I could have hoped for.

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