[HN Gopher] Hack NFL data using Postgres (and maybe win your fan...
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       Hack NFL data using Postgres (and maybe win your fantasy draft)
        
       Author : CoolAssPuppy
       Score  : 41 points
       Date   : 2021-07-27 19:58 UTC (3 hours ago)
        
 (HTM) web link (blog.timescale.com)
 (TXT) w3m dump (blog.timescale.com)
        
       | akulkarni wrote:
       | The blog post is interesting, but for anyone who wants to play
       | with the data themselves, instructions are here:
       | 
       | https://docs.timescale.com/timescaledb/latest/tutorials/nfl-...
        
       | autokad wrote:
       | has anyone found a data set that has all years? football it seems
       | kinda protected. its really easy to get all baseball data
        
       | swasheck wrote:
       | i've always wanted to test the hypothesis that the timing and
       | type of penalties within a game have more of an impact than the
       | overall number of penalties. is there a way to leverage a penalty
       | for strategic advantage at any given point in the game?
       | 
       | i still suspect that would be hard to determine given the
       | subjective nature of what constitutes a penalty and what
       | (dis)advantage the penalized team was carrying at any given
       | moment.
        
         | CoolAssPuppy wrote:
         | This reminds me of Belichick intentionally taking defensive
         | penalties to run out the clock.
        
       | avthar wrote:
       | Cool dataset! I wish there was a similar dataset for Premier
       | League football (or even international soccer). Does anyone know
       | of a good resource?
        
       | CoolAssPuppy wrote:
       | Today is opening day for most of the NFL's training camps. I'm a
       | huge fan of public datasets, and my coworkers and I happened upon
       | this dataset from the NFL. We loaded it into our company's
       | product (TimescaleDB) and did some number crunching. We wanted to
       | definitively answer some questions about whether or not there is
       | a quantifiable difference in performance when playing at Mile
       | High Stadium (there is) or if Tyreek Hill really is as fast as he
       | seems (he is). If you're a football fan, there's some good data
       | in there. At the very least, you may settle a few bar bets. Maybe
       | you'll even find something to help you win your fantasy league
       | this year.
        
         | Cyclone_ wrote:
         | What's the most interesting conclusion you were able to find
         | using the advanced data that you wouldn't be able to see with
         | the basic stats like QBR or yards per carry?
        
           | CoolAssPuppy wrote:
           | I was suuuuper curious about the fastest player on the field
           | (i.e., in full pads on game day), and the play-specific data
           | includes acceleration as one of its data points. Miranda on
           | our team (co-author of the post) dialed up a query to show
           | the top 3, one of whom is Tyreek Hill. (The other two don't
           | play that much)
        
           | CoolAssPuppy wrote:
           | Should add, I'm a big fan of all the football metrics
           | providers and follow them all religiously during the season.
           | The NFL dataset we found isn't as comprehensive, but it's
           | still really fun!
        
       | exdsq wrote:
       | This seems like a great way to get your NFL-loving ORM-crazy
       | colleagues into the world of SQL
        
         | akulkarni wrote:
         | It's also a great showcase of the power of SQL :-)
        
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       (page generated 2021-07-27 23:01 UTC)