Monday, May 11, 2015

Sunk cost and the NFL Draft

I’ve looked at the NFL Draft a lot since starting this blog. As the draft was here in Chicago this year, I found myself running into a number of jerseys on the street when I went out for lunch on Thursday and Friday. Even more surprising than the fact that people had travelled – in some cases from pretty far away according to the jerseys – was the fact that a lot of them were wearing jerseys of players who were disappointments if not outright busts. It got me thinking about sunk costs and whether teams are any better than their fans about cutting their losses.

To try to get at this we’ll need to know how much teams value their draft picks – conveniently we do know this via the Jimmy Johnson-popularized draft value chart – and then compare this to how much those players are used. Usage is a bit tricky but I’m going to approximate it with games started (1 full game) plus games played (2014 avg snaps non-starter / 2014 avg snaps starter, by position).

Before even getting to questions of usage, there is a significant disparity in the proportion of players from each round who end up making a roster.

Round
% on Roster Year 1
1
97%
2
94%
3
83%
4
81%
5
70%
6
62%
7
52%

I am guessing that most of this comes down to talent disparity, but there is certainly some aspect of sunk cost at work here. Lots of later round picks – to say nothing of undrafted players – never make it onto a roster to get into the rest of this analysis. They are, however, not the topic of this analysis. I want to see if a player’s draft value still impacts playing time even after making a roster.

The first cut of this is simply to look at draft weight and usage, checking how much the former impacts the latter. The regressions for each of a player’s first 6 seasons are below:

Usage vs Draft Weight



Draft Weight
Year
R^2
Intercept
Coefficient
P-Value
1
0.22
4.53
15.87
0.00
2
0.16
6.88
13.87
0.00
3
0.10
8.10
10.71
0.00
4
0.08
8.84
9.18
0.00
5
0.05
9.49
6.58
0.00
6
0.04
9.88
6.14
0.00

The draft weight is a significant variable throughout the first 6 years of a player’s career, but the strength of that relationship declines over time. The 1st year model explains 22% of the variation in usage while the 6th year model explains just 4%.