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Fantastic. Regarding data. I have weekly (actually, twice weekly, Thursday and Sunday) depth charts and injury reports, scraped from rotoworld.com. Only for 2015 though. LMK If this will be useful and I'll turn it into CSVs. And there's some charting data available here, going back to 2000, for a surprisingly reasonable price of $49.
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Feb 4, 2016 17:23
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Forever_Peace posted:Hell yes let's do this. I'll just give you the whole thing. Here you go: https://www.dropbox.com/s/vi0j9tt3r386v96/2015-weekly.hdf?dl=0 This is an HDF file so you can load it in Python with pandas.read_hdf (it was written by pandas, so this is the native format; you may have to install the extra package "tables"). You can also load it from R, although I've never tried: http://pandas-docs.github.io/pandas-docs-travis/io.html#io-external-compatibility I recommend you use a HDF viewer to browse the tree, but here's how it should be: <week>/<day (thursday or sunday)>/<source>/<description>. If the data requires further groupings, they are added on (there are a lot of projections here, and for many sites it was easier to scrape separately by position or by fantasy scoring system). For example: 01/sunday/rotoworld/depth 01/sunday/rotoworld/injuries 15/thursday/fantasypros/fanduel Hope that's enough info for you to get data out. Let me know if you have trouble.
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Feb 5, 2016 03:56
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Love the chapter! Turn this into a stats textbook and I will convince my university to shower you with that sweet, sweet textbook cash.
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Mar 2, 2016 17:04
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I'm teaching intro stats lab this semester, and I'm going to use your Richardson vs. Lynch example to start talking about sample size issues. Is the full text posted anywhere besides SA? I'd like to link it so that students can read the whole thing if they're interested.
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Sep 22, 2016 20:57
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Jekyll, the default system for GitHub pages, looks good and should be relatively easy to set up.
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Sep 28, 2016 16:54
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It's not free and I didn't check that it had exactly what you want, but I would be surprised if it doesn't (I think it has who was on the field for every play, not sure about roster status): http://armchairanalysis.com/ Certainly cheaper than the enterprise data vendors like STATS.1
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Jul 29, 2017 23:49
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