“Winning will solve our recruiting problems.”

“Recruits should be lining up to play at [Position]U.”

“Why would any WR/QB recruit want to play in this offense?”

We’ve all seen, and maybe even made, these and many other claims about recruiting on this site and elsewhere. We may even consider them conventional wisdom without questioning their validity. But are they, in fact, supported by the data? What factors weigh most heavily on a recruit’s decision to commit to a particular school? Is it possible to identify the correlates of recruiting and, if so, what are they and how strong of an effect do they have?

This is the first of what I plan to be a couple of diaries (spaced out over several months when I have time) that will subject these and other recruiting claims to empirical scrutiny. Today’s diary will go through some of the initial hypotheses that I plan to test, discuss the data, and then show some pretty graphs. I’m still collecting and merging some of the data for the independent variables, so the actual hypothesis testing will come in later posts.

 

INITIAL HYPOTHESES/RESEARCH QUESTIONS TO BE TESTED

Below are just some of the claims that I thought would be fun and feasible to explore. If you have any suggestions for additional tests, please let me know and I’ll look into the data availability, etc.

• Just win, baby: recruits are more likely to commit to programs with a recent record of success on the field.
• Get me to the Pros: recruits are more likely to commit to schools with a higher number of recent draft picks, first round draft picks, etc.
• [Position]U: recruits are more likely to commit to a school with a record of success at their particular position (draft picks, Heisman contenders, position-level stats, etc.).
• Distance matters: recruits are more likely to commit to geographically proximate schools, in-state schools, etc.
• Distance matters, unless you are Alabama and Georgia (alternative title: “fun with interactions”)
• Just how hard is it to pull a recruit out of SEC territory?
• Show me the money: I’m working on a way to see the effect of NIL. It’s gonna take some creativity…
• Any other suggestions?

Of course, these statements are not mutually exclusive. It’s possible that all, some, or none of them are supported by the data. And, I’ll admit, some of these relationships might seem so intuitive that they have become generally accepted or conventional wisdom. You may even wonder what is the use of testing, say, whether winning matters for recruiting. To that I would reply:

1. ‘Conventional wisdom’ is often wrong, and even the most basic claims should be subject to empirical scrutiny (remember, many thought general war was unthinkable on the eve of WWI).
2. Even if we ‘know’ that, say, winning has an effect on a recruit’s decision, it's still relevant to know how much of an effect it has.
3. It’s the offseason. And I’m curious. What else am I going to do with my spare time?

 

THE DATA

The hypotheses are all specified at the recruit level, suggesting some factors that will influence a recruit’s decision to commit to one school over others. Since it’s typically a good idea to avoid drawing inferences about individual behavior from aggregate data, the data need to be collected at the individual level.

The base data come from the 247 composite list of top-200 players in each recruiting class for the past 5 years (2019-2023). The data are organized by the recruit and the offer school. That is, for each top-200 recruit, there is a separate observation (row) for each P5 school that made a scholarship offer as listed on each recruit’s profile page on 247sports.com. For example:

Each recruit’s unique ID number and the ID for each offer school from collegefootballdata.com are included for easy merging of other datasets.

Altogether, the dataset includes 970 of the 1000 recruits from 2019 to 2023. Nine recruits are removed because they committed to non-P5 schools (I only include P5 offers and commitments). Missing data, either from 247 or collegefootballdata.com account for the remaining missing observations. One notable missing observation is Quinn Ewers, ruining my ability to test the relationship between mullets and commitments to OSU.

The total number of observations (n), which includes every P5 offer for every recruit, is 20,926.

I’ll attempt to attach the base dataset for anyone that is interested. I’ve never attached a file here, so hopefully it works. If it does work and you notice any errors, please let me know.

 

ANTICIPATED FAQ

Why only the top-200 recruits?

Primarily because I have a real job and this is just a hobby.

But another reason is to help differentiate offers from “offers”. The lower the ranking, the greater the chance that an offer school, especially the top schools, ‘cooled’ on a recruit rather than the reverse. I realize this is not always the case and that schools will often heavily recruit lower-ranked players, especially based on their own evaluations. But in the absence of being able to distinguish offers from “offers”, I use the top 200 as a proxy for ‘committable’ offers.

Why only P5 offers and commitments?

Because the vast vast vast majority of top-200 recruits choose P5 schools. Only 9 of the almost 1000 recruits in the data from 2019-2023 chose to go to a non-P5 school (4 to Jackson State, 1 each to Cincinnati, Houston, SMU, and UCF).

There is also the issue of making valid comparisons in later statistical analyses. Does a perfect season and (cough, cough) “National Championship” at, say UCF, mean the same to a recruit as a perfect season and National Championship at LSU or Georgia? Is Western Kentucky a more attractive destination than Ohio State for a QB recruit because their QB threw for the most yards in the NCAA and 1,000 more yards than CJ Stroud? Ultimately I want to be able to make ‘all else equal’ comparisons but, unfortunately, ‘all else’ is not equal in comparisons between the P5 and non-P5.

Why only 5 years (2019-2023)?

Seriously. I have a damn job.

 

WHAT DO THE DATA LOOK LIKE: DESCRIPTIVE STATISTICS

I’ll mainly present these without commentary since they are pretty self-explanatory and this post has already gotten a bit long. But I hope you enjoy them and that you find them informative. I first give some descriptives of where the top-200 recruits come from, and then where they end up committing.

All of the graphs below are also available here.

Where do the top-200 recruits from 2019 to 2023 come from?

The top-200 recruits by home state:

The top-100 recruits by home state:

Maps are also a nice way to visualize these data. Pay particular attention to the category values in the legend. As you can see from above, the data are pretty heavily skewed which makes the binning for the maps a bit difficult. If anyone has any suggestions for the future (I'm pretty new to creating maps), I'd be happy to hear them.

The top-200:

The top-100:

For people that like a little more granularity, I broke the top-200 down by the recruit's county (there would be much more bare space if I also showed the top-100):

There’s a pretty evident geographic orientation of the top 200, with the main hot spots in the south (especially Florida, Georgia, Louisiana, Alabama, and Texas) and SoCal. Among the northern states, Detroit stands out as one of the biggest recruiting hubs.

Where do the top-200 recruits commit?

First by conference.

The top-200 recruits:

The top-100 recruits:

It really is insane to see the number of top-200 recruits that the SEC is able to sign. Over all years, the SEC pulls in 43% of the top-200 and 49% of the top-100 recruits in the nation.

The next few graphs further break the top-200 and top-100 commitments down by the offense/defense position of the recruit.

The top-200:

The top-100:

The SEC definitely emphasizes defensive recruiting. In 2016, they pulled in 65% of the top-100 defensive prospects in the nation. Alternatively, the ‘defense optional’ Big12 consistently pulls in the fewest top-200 and top-100 defensive recruits, with the Pac12 close behind. With the exception of 2023, the Big12 generally gets about half as many of the top defensive recruits as the Big10.

The next graphs break down the destination of the top-200 and top-100 recruits by commitment school.

As if you needed more evidence that the SEC is a recruiting juggernaut, especially at the top. Just note that Alabama and Georgia alone have pulled in the same number of top-200 recruits (169) as the entire Big10 (169) and more than the entire Pac12 (111) or Big12 (103). If they had three more top-200 recruits, they would have matched the total haul for the ACC as well (172).

A big factor in the SEC’s recruiting dominance is undoubtedly the geographic concentration of top-200 recruits in the south. But to get a fuller picture, future posts will delve into the effect of a number of factors (location, distance, wins, draft picks, position success) to understand why the top-200 recruits choose to commit to particular schools.

Any comments/suggestions/requests for future analyses are appreciated.

Thanks for reading. Go Blue!