Our group has all agreed to work on sports data of some sort. We are currently interested in looking at the differences between NFL hall of fame wide receivers and non hall of famers. In particular we would like to identify players that appear qualified to be in the hall of fame as well as benchmarks that wide receivers could look towards for receiving inclusion in the hall of fame.
We would be using the 'nflwr_hist' section of the 'fivethirtyeight' package. After perusing the package it seems like the wide receiver data set also includes tight ends, so we might have to include that position as part of the analysis as well, or maybe find out why those players are in the data set and what their criteria are.
Data set link: https://cran.r-project.org/web/packages/fivethirtyeight/vignettes/fivethirtyeight.html
Another goal would be to try to get a normalized statistic which could compare players from all football positions and then look at whether the wide receivers entering the hall of fame are actually statistically more efficient than the linemen and running backs etc. This website has a fairly comprehensive list of positions and years, although we are unsure of how difficult it would be to get it into a neat R dataset:
https://www.footballoutsiders.com/stats/nfl/wr/2009
In summary, our overall goal is to examine wide receiver inclusions in the hall of fame. We plan to examine that through the following lenses: (1) Comparison to other wide receivers statistically to see if the included members really stand out. (2) Use a normalized statistic to compare the efficiency of hall of fame wide receivers to the efficiency of running backs, linemen, etc. to see if the proportion of inclusions is fair across all positions.
If our project needs additional depth we could also include the 'nflwr_aging_curve' subset of the same five thirty eight package, and look at the data with an additional lens, specifically age.