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Saturday, July 26, 2014

Newsweek: With Big Data, Moneyball Will Be on Steroids

More Statcasting…and the death of the amateur sabermetrician?

Another incentive for the league—particularly in the face of rising salaries—is an improved understanding of player value, particularly on the defensive end, where teams have focused more attention in the past few years. Defensive shifts, once only employed by the wonkiest teams, have become a league-wide staple thanks to advances in batted-ball data. The problem is, shifts or not, evaluating glove work remains difficult, as most teams rely on some combination of scouting reports, play-by-play data and manual charting. Statcast offers something better: a way to focus on a player’s defensive attributes—his reaction time, range, route efficiency and so on—rather than his results, which are influenced by too many independent variables to list. This potential has excited many outside the industry (especially with the promise that the data will be made public) and even more within.

The only negative to come from all the new technology could be the death of the hobbyist. An important consideration, because some hobbyists have done research that changed how people inside and outside the industry approach the game. For example, Mike Fast was working as a physicist when he used PITCHf/x data to confirm the long-held suspicion that catchers influence how umpires call balls and strikes. Fast is now employed by the Houston Astros. Because the new data are so unwieldy, the barrier to entry so high, only select outsiders will possess the computing strength and wits to scale the wall. In time, someone might make a discovery that eluded the industry. Otherwise, the real advances—those that change how teams are built and how strategies are employed—will happen behind closed doors.

Mike Emeigh Posted: July 26, 2014 at 09:22 AM | 7 comment(s) Login to Bookmark
  Tags: analytics, moneyball, sabermetrics

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   1. kthejoker Posted: July 26, 2014 at 01:58 PM (#4758078)
Is the new data that unwieldy? Or for that matter that big?

Defense wise...

Maybe 40 pitches in play per team per game. 9 defenders to track per pitch. Roughly 200 games a year with spring training and playoffs. That's only 72000 samples of individual play variables (60% or more of which on any typical given play are useless) for evaluation. Even if you add sub play granularity and some form of multivariate combinatorics you're looking at most a million or two rows of data, should be pretty easy to crunch.
   2. bigglou115 is not an Illuminati agent Posted: July 26, 2014 at 04:13 PM (#4758149)
I think it's more a concern of what we have access to. We were never supposed to have pitch f/x, I'm dubious we'll have full access to all the new defense stuff. How can the "hobbyists" keep up when teams have access to information that's more descriptive and plentiful than we have?best case scenario a BPro or someone pays to join whatever subscription service is offered and we get snippets through whatever filter they apply.
   3. snapper (history's 42nd greatest monster) Posted: July 26, 2014 at 04:42 PM (#4758158)
Is the new data that unwieldy? Or for that matter that big?

No. A lot of "big data" is just a marketing sheen placed over pretty standard analytics.

I mean, the credit card companies have been analyzing hundred of transactions per year, for tens of millions of cardholders for decades, w/o any "big data".
   4. f_cking sick and tired of being 57i66135 Posted: July 26, 2014 at 05:16 PM (#4758165)
so, i have several ideas about ways to use pitch f/x, but i have no idea where or how to begin working with that data.

is there anyone here who could point me in the right direction?

thanks.
   5. cardsfanboy Posted: July 26, 2014 at 06:30 PM (#4758196)
so, i have several ideas about ways to use pitch f/x, but i have no idea where or how to begin working with that data.

is there anyone here who could point me in the right direction?

thanks.


Buy this book.

This is an excellent book on using R, you need to be a bit comfortable with computers to really use this as it's not the most instructive book I've read, but it does provide you with a good ability to analyze data. It's useful with pitch F/X, retrosheet and the Lahman database.
   6. f_cking sick and tired of being 57i66135 Posted: July 27, 2014 at 12:57 AM (#4758286)
Buy this book.

This is an excellent book on using R, you need to be a bit comfortable with computers to really use this as it's not the most instructive book I've read, but it does provide you with a good ability to analyze data. It's useful with pitch F/X, retrosheet and the Lahman database.
looks like it's worth a try. thanks.
   7. An Old Leaf Posted: July 29, 2014 at 06:09 PM (#4759947)
I bet you didn't know someone could love you this much.

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