My Crappy Fantasy Football Draft

September 22, 2010
By

[This article was first published on The Log Cabin » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I compared the results of my fantasy football draft with the results of more than 1500 mock drafts at the Fantasy Football Calculator (FFC).  I looked at where player X was drafted in our league, subtracted off the average draft position on FFC, and divided by the standard deviation of the draft positon of that player on FFC.  In other words, I’ve computed a ‘standardized’ draft position for the given player.

How do we interpret this standardized draft position?  Obviously if we have a positive score, then a player was drafted later in our draft than the average position on FFC.  This would mean that a team owner in our league got a pretty good deal on that player.  Understand?  Divided by the standard deviation just places all of the draft positions in a standardized unit for comparison purposes.  Here are the results of our draft.

What do we see from this?  Well, my draft sucked.  Most of my boxes in the heat map are negative!  So I drafted my players a little higher than the average draft position on FFC.  In particular, it looks like I picked Pierre Thomas way earlier.

Some positives:  Yurcy picked Randy Moss with the 18th pick and his average draft position on this website was 8.8.  Possibly the biggest winner was Rob’s 6th round pick of Wes Welker…good value there.

I’ll do the same for my league with the boys in Vermont.  Hopefully the results are a little better than what I did with the Princeton gang.

The code is published at github under ffdraft.

To leave a comment for the author, please follow the link and comment on their blog: The Log Cabin » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)