The whole process is split into 3 notebooks:
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Scraping all expert draft rankings
Start out by first scraping the FP expert list, and then using that list to scrape each expert's rankings.
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Filtering and summarizing expert rankings
Now that all of the expert ranking data is downloaded and saved, I use pandas to calculate mean/median rankings and then rank by position. Finally, it's all saved to a spreadsheet.
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Finally, take all of the summary rankings and combine with the raw expert ranks to produce nice Seaborn plots in PDF format for easy crossing-out on draft day.
Here's a quick preview of what the plots look like: