The biggest names in the transfer portal have mostly made their decisions, and my weekly power conference previews begin this week. It sounds like a pretty good time to post some updated SP+ projections!
Thus far, my preview series has leaned on numbers posted in February after the second national signing day had come and gone. But enough has changed at this point — I was getting ready to write a Pac-12 South preview using numbers that thought quarterback Jayden Daniels was still at Arizona State, for instance — that it felt like a good time for an update. These aren’t the final projections of the offseason; those will still come in mid-to-late August. But let’s see what havoc the transfer portal hath wrought in the past three months.
A quick reminder: Preseason projections are based on three factors.
1. Returning production. The returning production numbers are based on rosters I have updated as much as possible to account for transfers and attrition. The combination of last year’s SP+ ratings and adjustments based on returning production makes up more than two-thirds of the projections formula.
2. Recent recruiting. This piece informs us of the caliber of a team’s potential replacements (and/or new stars) in the lineup. It is determined by the past few years of recruiting rankings in diminishing order (meaning the most recent class carries the most weight). Beginning in 2022, this category also is impacted a bit by the recruiting rankings of incoming transfers. This is a new thing, and I’m not giving it much weight right away, but it will have a slight impact. This piece makes up about one-fifth of the projections formula.
3. Recent history. Using a sliver of information from previous seasons (two to four years ago) gives us a good measure of overall program health. It stands to reason that a team that has played well for one year is less likely to duplicate that effort than a team that has been good for years on end (and vice versa), right? This is a minor piece of the puzzle, but the projections are better with it than without.
(One other reminder: SP+ is a tempo- and opponent-adjusted measure of college football efficiency. It is a predictive measure of the most sustainable and predictable aspects of football, not a résumé ranking, and, along those same lines, these projections aren’t intended to be a guess at what the AP Top 25 will look like at the end of the year. These are simply early offseason power rankings based on the information we have been able to gather to date.)
Now to the list! The change column represents how much a team’s rating has changed since February (the change in ranking is in parentheses). These changes are due primarily to either transfers or the simple fact that, when I posted the February rankings, less than half of FBS had posted official updated rosters for 2022. Over the past three months, I found that some rosters had far more losses than anticipated.
Here are the full rankings:
Biggest moves
Fourteen teams have seen their projections rise by at least one adjusted point per game:
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Ball State +3.4 (its ranking improved by three spots)
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USC +2.8 (up 13 spots)
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San Jose State +2.7 (13)
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LSU +2.1 (nine)
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Oregon +1.5 (eight)
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New Mexico State +1.4 (zero)
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Kansas +1.3 (six)
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Virginia +1.3 (eight)
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Nevada +1.3 (three)
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Coastal Carolina +1.3 (eight)
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Alabama +1.2 (one)
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Oklahoma +1.1 (two)
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Miami +1.0 (six)
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Akron +1.0 (three)
For teams like Ball State and SJSU, simply getting an accurate read of their roster made a big impact, but for others near the top — namely, USC and LSU — the portal has made a huge difference. But has it made enough of a difference in the projections? We’ll come back to that in a moment.
As you might guess, at the moment it’s easier for a team’s projections to fall by quite a bit because of the portal than to rise. Here are the 13 teams whose projected rating has dropped by at least 2.5 points since February:
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Wyoming -6.5 (down 19 spots)
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James Madison -6.2 (-17)
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Georgia Southern -4.2 (-9)
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Texas State -4.1 (-5)
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UTSA -3.4 (-12)
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Central Michigan -3.3 (-7)
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Houston -3.3 (-9)
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Arizona State -3.3 (-11)
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Baylor -3.2 (-10)
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FIU -3.2 (-3)
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West Virginia -2.9 (-9)
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Stanford -2.7 (-9)
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Maryland -2.5 (-6)
Wyoming has been hit very hard by transfers and now ranks 129th in returning production, down from 112th in February and ahead of only conference mates Hawai’i and Nevada. FBS newcomer James Madison, meanwhile, dropped when I put together what I feel is a more accurate look at the program’s recent recruiting.
The USC-LSU conundrum
Simply perusing teams by the eye test, by far the two rankings that stand out the most are those of No. 53 USC and No. 36 LSU. (SP+ is a pretty big Tennessee believer, so that one might have popped out at you, too.)
I am assuming that both USC and LSU will outperform their projections, perhaps by quite a bit, as both have enjoyed massive gains in the transfer portal. New USC head coach Lincoln Riley completely revamped the Trojans’ offense by adding Oklahoma quarterback Caleb Williams, Pitt receiver Jordan Addison, Oregon running back Travis Dye and many others, and while his 10 additions on defense have not been quite as eye-popping from a stars perspective, they’re still voluminous. These projections take both these new players’ 2021 production and recruiting rankings into account, but USC’s dismal recent performance — the Trojans plummeted to 82nd in SP+ last season — is still dragging the team’s overall numbers down. The Trojans are projected to improve by nearly 30 spots, which is enormous, but they’re going to be a preseason top-10 team in the AP poll.
New LSU head coach Brian Kelly has made similar changes, bringing in Arizona State quarterback Jayden Daniels, at least one transfer for every unit on the field and completely transforming the Tigers’ secondary, losing five of last year’s top six but bringing in five transfers. LSU will almost certainly be ranked relatively high in the AP poll this year as well, but after ranking 45th and 65th over the past two seasons, the Tigers get only so much benefit of the doubt from SP+.
Once we have dealt with a couple of years of evidence in how teams loading up on transfers change their ratings from year to year, I will get a pretty good idea of how to account for this in the projections. This is a very new phenomenon, however, and I don’t want to overreact in how I account for this, so for now we’re just going to have a couple of weird outliers.