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  • Captainjustice

    Hey guys, I’m trying to improve my game a little by constructing a spreadsheet with data to look at for each sport. Trying to see if y’all can give me a few pointers on what sites would be the best to pull from and what particular stats I should focus on. I know it’s a broad range question but any help would be much appreciated 😊

  • TheDataDetective

    • Blogger of the Month

    @Captainjustice said...

    Hey guys, I’m trying to improve my game a little by constructing a spreadsheet with data to look at for each sport. Trying to see if y’all can give me a few pointers on what sites would be the best to pull from and what particular stats I should focus on. I know it’s a broad range question but any help would be much appreciated 😊

    Are you planning to do it manually or will you write some code?

  • Captainjustice

  • TheDataDetective

    • Blogger of the Month

    Not sure about the other sports, but my app gets all of its player data directly from MLB.com. It requires a bit more effort than some of the other sites that provide “finished” stats, but you can download play-by-play logs of every historical game (in XML or JSON) and generate whatever stats you’re looking for down to the most granular level. Every stat that you find on MLB.com comes from this same data. It takes some effort, but it doesn’t get any better than this in terms of completeness and flexibility. I wish every major sports league offered something similar.

    As far as which stats to look at, everyone has his/her own opinion on this and it’s an ongoing debate. I personally find that there are too many types of stats in baseball and, while interesting, are very difficult to consolidate into something useful for DFS purposes (e.g. player projections). Therefore, I generate my own FPTS per plate appearance stats for various types of splits and use these as a major input into my player projections. I have had success with this approach and it makes sense because it incorporates all of the other stats but in a normalized, DFS-oriented way. There are admittedly some issues (particularly when it comes to the xBLAH stats that attempt to predict future player performance), but it’s easily incorporated into a projections algorithm and is strongly correlated to real player performance. (I have thoroughly tested this with back-testing of my algorithm to verify). Anyway, this is a much longer discussion so I will cut myself off here.

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