If you're interested in playing around with recruiting data from as far back as 1980, there are currently spreadsheets available for download here:
This fella's an NC State fan with one hell of a passion for barbeque, and an astounding collection of hikes on his page, too. Like, seriously, this guy hikes a lot and it's pretty awesome. (I've warned him in advance that a bunch of random Hokies might be poking around his site).
Long term, I have submitted this data to the redditor who runs this site as well. He's having a hell of a busy summer, but the plan is to upload all of this data for use with the optimized search and tool options on his site.
Long story short, I took a couple of years coinciding with the start of the pandemic to obtain, scan, edit and sort individual signee/recruiting data I found on eBay. I basically determined how the 247 Composite worked and then retroactively applied this format to create a database. In the following sections I'll describe what data there is in each spreadsheet, and I've added a few graphs to show how the data can be sorted and used. (I display the graphs showing Hokie curves where many are available- links are provided to the other graphs if you're interested in perusing them.)
Fig 1.1: 114,062 Signee Scores plotted across 43 signing classes, highest to lowest
This spreadsheet has by far the most data, but there really aren't a ton of ways of graphically representing this. All of the Team Data comes from the individual signee data in this spreadsheet.
Fig 2.1: Signee threshold scores by season
Fig 2.2: Signee STAR score by season, per-centage
Fig 2.3: Database Teams & Graded signees by year
These graphs kind of show a blueprint of how the data looks before the internet era and after. Basically, before the internet, you'll typically only find evaluations on ~1/2 of the FBS signees. So with the older data, all of the unrated players end up having the same score, something I started calling the "Floor". I used this as the threshold for 2-3 star players. Starting in about 2006, most of the FBS signees started having some kind of individual score. From this point onward, there are far fewer "2-Star" signees in the database.
There are still signees without evaluations today; in fact COVID seems to have temporarily bumped up the number of players that weren't evaluated well enough to have a Composite score. These players simply don't have scores associated with them- and they don't affect a team's score at all. This most notably affects JMU's introductory FBS class (2022). They have 4 unranked signees. Even though they have 8 rated transfers, Transfers don't factor into team recruiting scores. So JMU's 2022 signing class effectively has no class score.
Fig 2.4: Total FBS Teams and FBS Signees by season
Fig 2.5: Average, Min & Max signees per class by season
These graphs show a bit of how college football has looked over the years, and how this has affected this database. I list MOST of the FBS programs, but essentially I've omitted all of the football programs that don't use scholarship rules and limits. This means that the Ivy League (1980-81) and the Service Academies (all seasons) don't appear at all in my database. The service academy's signing classes vary wildly, even into the internet era they didn't publicly release their signing classes. They aren't really competitive for Blue Chip recruits- basically they give full rides to a whole lot of well-rounded individuals- many of them are very good athletes, so their classes are full of respectable ** "signees" and some seasons they'll "sign" a couple of *** players, too.
In 1981, the NCAA had a purge of schools that didn't meet the requirements to compete in Division 1A. The Southern, Southland, Ivy League and (eventually) Missouri Valley conferences dropped down to FCS starting in 1982. In 1992 the scholarship limit for FBS (Div 1A) dropped from 95 to 85 per school. 1989 was the start of this transition, so basically an average signing class went from 25 signees to 22.5 over this period.
We're currently in a new adjustment period with the Transfer Portal (coupled with the Covid eligiblity queue from the 2020 season), so by 2025 or so a new average signing class size should be apparent. (Probably end up somewhere just shy of 20).
Fig 2.6: OVERALL signees by top producing States (VA is on the second graph)
Fig 2.7: BLUE CHIP Signees by top producing States (VA is on the first graph)
While it might seem like OVERALL signees by state is a useful metric to use to determine which states are producing the most talent, the truth is that it really isn't. When Richmond and William & Mary dropped down to the FCS in 1984, the number of signees from the state of Virginia plummeted. This was not a valid indictment of Virginia High School Talent. The recruitment of 2 and 3-Star players is simply based on geographic convenience. If North Dakota State were to jump to the FBS, there would suddenly be a half dozen signees or so from that state every year (which is about a half dozen more on average than there are now).
Blue Chip production is the measure to use to determine how productive the states are over time. Those players are getting signed by somebody somewhere, with little regard for the geographical appointment of available FBS schools across the nation.
Fig 2.8: P5/G5 split, Teams and signees
In 1980, there were similar numbers of Auto-Qualifying programs (P5 and equivalent Independents) and Non-AQ (G5) programs. Following the purge of 1982, the number of G5 programs dropped substantially, and over the course of the next four decades has essentially grown back again.
Over this time, the number of P5 programs has been pretty consistent, hanging out around 65.
Fig 3.1: Average Team Scores from #41-50 (VT is ranked #44 from 1980-2022)
For the Team Data Spreadsheet, I calculate team scores 3 different ways. First, I basically made an "Estimator" of the 247 Composite Team score. I don't like this method, so I also include the Raw Average score of the signees, and an "Adjusted" average score, which is the method I prefer (and shows up on these graphs).
In truth, I'm still being deferential to 247 Sports, as this "Adjusted Average" team scoring method actually shows up in their Team Scoring explanation:
Fig 3.2: 247 Sports Team Score Formula
First off, 247 Sports doesn't even use this method anymore; they changed their methodology a season after they introduced the Team Score Calculator. Basically, this old method only really counted the top third to half of your class. But pay attention to that "C". (They stopped factoring in that "C" with their new method, BTW.)
Fig 3.3: A 3D image that 247 Sports provides to show their old methodology
Fig 3.4: A 2D representation of how that old method actually affects the tabulation of a team score
So they opted for a new methodology that would change the team score no matter where a new signee was added to a team (obviously a higher scoring recruit moves the needle much more).
Fig 3.5: A 2D approximation of the "New" 247 Sports team scoring
So back to my favorite- it's similar to taking the raw average. I just figure out what size the average signing class was each season (lately that had been 22 or 23 players a class), and simply taking the average of the top 22 or 23 players for a signing class.
That's the "C" from above.
There's a small advantage for larger classes & no penalty with small classes. Basically, most every program is pretty good at keeping 85 scholarship players on a roster. So class size from year to year is, for the most part, irrelevant. Teams that consistently have large classes are simply more actively managing, or churning their roster. So they get a little bump for this, but for the most part average recruit rank is still the best method of determining how programs are doing from year to year.
Fig 3.6: ACC Recruiting Trends
Fig 3.7: Big East/AAC Recruiting Trends
Fig 3.8: Middle & Minor Independent Recruiting Trends (VT was a MIDDLE independent)
These graphs show the team scores across the various conferences. Typically, where conferences change I showed the current conference in BOLD and the other conference affiliations in some manner of dotted or slashed lines.
When I was starting out this project, I tried to sort all of the early FBS independents into P5/G5 categories. I found that Independence was more of a spectrum, and I used recent schedules and opponents to determine "peers" for the Minor (G5), Middle and Major (P5) programs. Virginia Tech was a Middle Independent using this method; we were pretty split between playing other G5 and P5 teams (but less than half P5 opponents, or peers). Basically, for these teams, any conference shakeup could go either way. And in truth, it did.
When I developed team scores, I ended up grouping the Middle independents in with the G5 schools (they basically recruit in the middle, though- however with no conference affiliation in the TV era, they were always at a disadvantage.
In 1997, the last Middle independent (ECU) joined the CUSA, so that category went away. After this, you were either Notre Dame or you were tiny. Until BYU went independent, that is. I didn't reintroduce this category into the database, but I dissected this for a Reddit thread about a year ago and discovered that BYU would have essentially been a "Middle" independent using this same peer/schedule methodology.
EDIT: PS, I made this graph to show how the conference recruiting has changed historically, with a graph that shows how I would project the new conference alignments to change in the future:
Fig 4.1: Historical and Projected Conference Recruiting Trends