Earlier in the month, I posted a picture on social media comparing fantasy football team points compared with their draft position.
— Person (@ergosum_person) July 24, 2017
I thought I found a clear pattern that could help fantasy football managers use data to understand that the 10th pick is actually not that bad in a snake draft.
The plan was simple. Download samples from 2008 to the present on fantasy football and create a quick “fact sheet” for people to use going into the draft. Once I got more data I realized my original plot was lucky and simplistic.
The real data is far more dependent on the quality of players.
A Quick Look into Fantasy Football Team Stats
Here’s a list of things I’ve found — it’s small:1)All the analysis is done samples from 10-team public leagues on Yahoo Fantasy Football.
- Draft position alone doesn’t mean much without accurate player rankings
- ~11 roster moves is the sweet spot
Draft Position versus Fantasy Points
Draft position is a lot more nuanced than I first thought. To do solid analysis we’d need data on pre-draft rankings and fantasy player scoring. It’s out there but would take a while to acquire
Takeaways I see:
- The best teams have ~11 roster moves — look at the shaded spots with the most fantasy points
- Correlation is not causation! This is probably because managers have to compensate for bad teams by increasing the number of moves.
- Teams that make no roster moves could do better by making a few moves
- You probably won’t have the best team if you make over 12 moves but you can still be good.
Like I said, I was hoping to use the data to learn more. I think it’s possible to go more into draft results but you’d need data2)Read my sports data guide on how fantasy players performed versus pre-draft rankings (Here’s a good place to get started http://fantasyrundown.com/2016-fantasy-football-rankings/ change the year in the url to see more).
If you want to take a look at the data yourself
- I’ve published the dataset
- The data scraping scripts and my analysis are all available on my git repo
- I used the Yahoo Query Language to extract the data
References [ + ]
|1.||↑||All the analysis is done samples from 10-team public leagues on Yahoo Fantasy Football.|
|2.||↑||Read my sports data guide|