*NSFL Contract Value

speculadora · (This post was last modified: 01-18-2018, 12:25 PM by bovovovo.)

The goal of this analysis was to uncover the NSFL's most valuable contracts. Before getting into anything, most valuable is defined here as creating the greatest surplus value. Surplus value over what? That's where the analysis comes in. My initial idea was to gather the following data points for each player: Position, Team, TPE, and average annual contract value (AAV) and regress the former three on AAV to create a sort of predicted contract value. I used the players and TPE totals from each team's roster subforum and got contract numbers from each team's budget thread. Only 6 teams had threads so that's the sample we'll be looking at. I encountered a substantial issue pretty early on, however. A considerable number of the league's highest TPE earners are getting paid near-minimum salaries. Here's what this looks like in a scatter plot.

[Image: PuNxcm0.png]

The reasonable assumption would be that, if nothing else, TPE and AAV should have a reasonably strong correlation. Obviously they don't. This sort of throws the regression idea out the window and forced me to adjust and create my own predicted AAV. I figured a reasonable way to do this would be to tally the total TPE and contract values for each team and determine a weighted AAV based on the player's TPE as a percentage of his team's total. The formula is basically this:

Projected AAV = (PlayerTPE / TeamTPE) * TeamAAV

Here is a scatterplot of TPE (x-axis) and projected AAV (on the y-axis as AAV_Team)

[Image: Pf7Wkl8.png]

Now there is a visible correlation between TPE and AAV. This, of course, can't be used in a regression because we know the formula used to explain all variance in the data, but it does provide a reference point for "value". I took the difference between the player's projected contract and actual contract to calculate surplus value generated by that contract for that player's team. Here is a table of the 9 players who generated $2 million or more in surplus value for their team.

[Image: fF5z2vt.png]

There are some pretty obvious limitations here. For one, it seems as if GM's can take a max of $1M and they tend to have fairly high TPE players, which means they'll tend to have the greatest surplus value. It also disregards position entirely. This could be projected with a similar method, but the formula would use position total TPE and total AAV rather than team totals. I didn't do that here, but maybe in a future analysis. It also does not give any consideration to rookie contracts generating future surplus value as their players improve, nor does it consider contract length (outside of the denominator for AAV). Hopefully this is at least a little bit interesting. If players on teams not included here have any interest in seeing how they stack up I would be happy to upload my data into a google doc that people can edit as they see fit, though it would require all of your team's contract and TPE data. I've also included the full table of surplus values below.

[Image: H9Qdvzw.png]

Side note: I'm not 100% sure if there's a limit to tasks you can do in a week. I already did a media a few days ago so if that interferes with anything just ignore this until the next grading period.

GRADED