Let’s see what Italian economists have to say about college football recruiting rankings

1.

We’ll begin this class by quoting Wikipedia:

The Pareto principle (also known as the 80/20 rule, the law of the vital few, or the principle of factor sparsity) states that, for many events, roughly 80% of the effects come from 20% of the causes. Management consultant Joseph M. Juran suggested the principle and named it after Italian economist Vilfredo Pareto, who noted the 80/20 connection while at the University of Lausanne in 1896, as published in his first work, Cours d’économie politique. Essentially, Pareto showed that approximately 80% of the land in Italy was owned by 20% of the population.

2.

For a while now, I’ve had the word “Pareto” on my long-term to-do list. I’ve wanted to see if this principle holds true in football recruiting. I can tie anything in the world back to football.

3.

I pulled in the roster/recruiting data from my 2018 previews and basically ranked the top 17 players on the roster, per the 247Sports Composite (because 17 is 20% of 85 scholarships). I also made the following adjustments to those Composite ratings:

• If you were unrated in the Composite, I assigned a 0.6800 rating. The lowest you’ll find for FBS recruits in general is a 0.7000, so that seemed to make sense for walk-ons I deemed worth listing in the previews. But this doesn’t really matter because not even service academies will have unrated recruits in their top 17. I just felt like sharing.
• I added a multiplier based on which unit you play on so that each unit carries the same average. (For 2018 rosters, the average Composite rating for WR/TEs was 0.8245, DLs 0.8231, QBs 0.8231, DBs 0.8192, LBs 0.8188, RBs 0.8188, and OLs 0.8184. So I adjusted it so that they’re all 0.8208 — the midpoint.)
• I also made an adjustment based on whether you’re on offense or defense. Why? Because recruiting rankings for defenders always have stronger correlations to performance than rankings for offensive players. So based on correlations, your rating is multiplied by 1.04 if you’re a defensive player and 0.96 if you’re an offensive player. That means that quite a few defensive players ended up with an Adjusted Composite rating over 1.0000, which is also fun.

4.

The correlation between the 2-year recruiting rankings I used for 2018 S&P+ projections and the current year-end 2018 S&P+ rankings was a solid 0.609. That’s a strong correlation, and it’s why I use recruiting rankings in my projections.

5.

The correlation between these new Pareto recruiting rankings and 2018 S&P+: 0.640. Better.

6.

Take out the massively underachieving USC and FSU, and it rises to 0.661. Jerks.

7.

I also looked at the the average 247 rating for the top 13 non-freshmen on your roster, since even star freshmen rarely play massive roles, and since 13 is about 20 percent of your non-freshman roster on average. The correlation between this top-13 average and 2018 S&P+: 0.633. Still better than the old way but not quite as good (or easy!) as just taking the overall top 17.

8.

Taking out the mid-majors, who are always a different story for obvious reasons, the top 12 P5 teams in S&P+ this year were Alabama, Clemson, Georgia, Oklahoma, Michigan, Notre Dame, Ohio State, Washington, Penn State, Mississippi State, Florida, and LSU. All were in the top 22 of these Pareto rankings, and 10 of them were in the top 15.

9.

The first major P5 outlier: MIZZOU, BABY. 13th-best P5 team per S&P+, 37th in the Pareto rankings.

10.

Why might it be more accurate to do it this way? For one thing, it’s serving a different purpose than the two-year rating. I use two-year averages in the S&P+ projections because it asks a follow-up question to “What production are they returning?” It basically gets at “How good are your new starters?” Using five-year recruiting averages correlates slightly better to S&P+ (0.619), but that, too, is looking more at roster talent than the talent of new contributors.

11.

Still, this Pareto average appears to be even better than the five-year average. Why? For one thing, it accounts for transfers, both in and out. If you sign blue-chippers and then lose them to transfers (looking at you, Auburn), you don’t get propped up as much. If you bring in a lot of transfers (hello, Houston and WVU), then doing this will more accurately read the talent on your roster.

12.

You want to see the data? HERE’S THE DATA.

13.

Not a massive difference, by any means. Using this method would have still resulted in S&P+ projections missing wildly on USC and FSU. There are always some drastic underachievers, obviously. But if it makes the projections better, it makes the projections better, so I’m going to play with this some more.

14.

That Pareto should have charged a monthly subscriber fee.