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Bill Connelly
In 93 days, it all starts again. From Week 0’s Irish Farmageddon (Iowa State vs. Kansas State in Dublin) in mid-August to the national title game in late January, the 2025 college football season looms. And with transfer portal movement finally slowing down — including spring moves, FBS teams have averaged more than 19 transfers this offseason, up more than 40% from last season — we can finally take a semi-confident look at what’s in store this fall. That means updating our numbers.
Below are updated SP+ projections for the coming season. 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 humanly possible to account for transfers and attrition. The combination of last year’s SP+ ratings and adjustments based on returning production makes up about 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). This is also impacted by the recruiting rankings of incoming transfers, an acknowledgment that the art of roster management is now heavily dictated by the transfer portal.
3. Recent history. Using a sliver of information from the previous four seasons or so gives us a good measure of overall program health.
(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 lines, these projections aren’t intended to be a guess at what the AP Top 25 will look like at the end of the season. These are simply early offseason power rankings based on the information we have been able to gather.)
Here are the updated rankings:
This time around, I am also experimenting with what you might call a fourth projection factor: coaching changes. Using data discussed in this March column, I have incorporated some adjustments based on who changed head coaches and/or offensive or defensive coordinators and how those teams performed against historic norms last year. Translation: For teams or units that underachieved significantly against their 20-year averages and changed coaches or coordinators (example: Oklahoma’s offense, Purdue’s entire team), that means a slight bump upward. For teams or units that overachieved and lost their coaches or coordinators (example: UNLV as a team or Louisiana Tech’s defense), that means a bump down.
The adjustments aren’t enormous, but when you see that Oklahoma’s projected rating has risen since February, that explains it.
Minimal changes near the top
Thirteen teams moved up or down at least 10 spots compared to February’s rankings, due to either transfer portal addition/attrition, the coaching adjustments mentioned above, or simply me getting a much better read on returning production after official roster releases. At the very top, however, not a ton changed. The top four teams from February continue to occupy the same spots, though Texas hopped Notre Dame and Oregon into the No. 5 hole. Clemson and Michigan rose a bit, Tennessee dropped five spots after Nico Iamaleava’s transfer, and Oklahoma eased into the top 15. (With their ridiculous schedule, however, the Sooners’ projected win total still isn’t great.)
The overall conference hierarchy hasn’t changed much either, though with the Sun Belt getting hit particularly hard by spring transfer attrition, the AAC moves into the top spot among Group of 5 conferences.
Average SP+ rating by conference
1. SEC (15.3 overall, 33.1 offense, 17.8 defense, 60.7% average returning production)
Top three teams: No. 2 Alabama, No. 4 Georgia, No. 5 Texas
2. Big Ten (9.5 overall, 29.1 offense, 19.6 defense, 56.7% average returning production)
Top three teams: No. 1 Ohio State, No. 3 Penn State, No. 7 Oregon
Both the SEC and Big Ten boast three of the projected top seven teams, but if we measure conferences by average ratings, the SEC still has a commanding lead due, as always, to the lack of dead weight. Only two of 16 SEC teams are projected lower than 43rd overall, while the Big Ten has six such teams, including three ranked 70th or worse. That helps explain why, despite playing only eight-game conference schedules, SEC teams occupy 13 of the top 15 spots in the strength of schedule rankings.
3. Big 12 (6.3 overall, 31.0 offense, 24.7 defense, 61.8% average returning production)
Top three teams: No. 18 Kansas State, No. 22 Arizona State, No. 26 Texas Tech
4. ACC (5.0 overall, 30.8 offense, 25.8 defense, 59.2% average returning production)
Top three teams: No. 8 Clemson, No. 12 Miami, No. 20 SMU
We see a similar dynamic with the Big 12 and ACC — in terms of the quality of its top teams, the ACC (three top-20 teams) seems to have an advantage over the Big 12 (one top-20 team). But the Big 12 has eight top-35 teams compared to the ACC’s four, and while no Big 12 team is projected lower than 66th, the ACC’s average is dragged down by three teams ranking 79th or lower.
5. AAC (-7.8 overall, 26.0 offense, 33.8 defense, 49.4% average returning production)
Top three teams: No. 48 Tulane, No. 53 Memphis, No. 63 UTSA
6. Sun Belt (-8.1 overall, 24.9 offense, 33.0 defense, 46.3% average returning production)
Top three teams: No. 49 James Madison, No. 74 Louisiana, No. 76 South Alabama
7. Mountain West (-8.6 overall, 23.5 offense, 32.1 defense, 46.5% average returning production)
Top three teams: No. 33 Boise State, No. 75 UNLV, No. 83 San Jose State
Three G5 teams are within one point of each other on average, though again, the distribution varies significantly by conference. The MWC is propped up significantly by Boise State, the best projected G5 team, but its average is dragged down by three teams ranking 119th or worse. The Sun Belt has only one such team. The AAC, meanwhile, has a solid five teams in the top 70 … and four teams projected 120th or worse.
8. Conference USA (-13.0 overall, 20.4 offense, 33.4 defense, 50.7% average returning production)
Top three teams: No. 69 Liberty, No. 85 Western Kentucky, No. 104 Jacksonville State
9. MAC (-13.7 overall, 19.8 offense, 33.5 defense, 41.1% average returning production)
Top three teams: No. 72 Toledo, No. 80 Ohio, No. 91 Buffalo
No conference was hit harder by the portal than the MAC, which has only three teams ranked higher than 94th in the returning production rankings below. That’s going to wreck your averages, though Toledo and Buffalo both escaped too much damage in this regard.
An approximate CFP contenders list
My SP+ strength of schedule ratings are based on a simple question: How would the average top-five team fare against your schedule? Oklahoma’s schedule currently features five of the projected top 11 teams and nine of the top 25, while Notre Dame’s features only two teams projected higher than 30th; SP+ SOS says a top-five team would average a 0.757 win percentage against OU’s schedule (equivalent to 9.1 wins in 12 games) and a 0.894 win percentage against Notre Dame’s (10.7 wins). That’s a pretty big difference.
Schedule strengths obviously vary quite a bit within conferences — not every SEC schedule is Oklahoma’s — but it’s worth acknowledging that when it comes to potential College Football Playoff-worthy résumés, the bar can be set in a different spot based on a team’s conference.
Average strength-of-schedule rating per conference
SEC 0.799 (9.6 wins for a typical top-five team)
Big Ten 0.846 (10.2)
ACC 0.891 (10.7)
Big 12 0.902 (10.8)
AAC 0.956 (11.5)
Sun Belt 0.958 (11.5)
MWC 0.959 (11.5)
CUSA 0.964 (11.6)
MAC 0.965 (11.6)
When it comes to how a top-five team would fare, the average SEC schedule is about one win harder than the average ACC or Big 12 schedule. The Big Ten, with its deadweight teams, is about a half-win harder than those leagues but is still more likely to get lumped in with the SEC than the others in the Power 4.
Long story short: We can confidently say that any 10-2 or better team in the SEC or Big Ten would be a likely playoff contender, just as any 11-1 or better team in the ACC or Big 12 would be. We can therefore create a loose list of likely CFP contenders by looking at the teams most likely to hit those marks.
Odds of an SEC team going 10-2 or better: Alabama 65% (SOS rank: 11th), Texas 61% (12th), Georgia 61% (13th), Ole Miss 38% (23rd), Tennessee 33% (24th), LSU 30% (ninth), Florida 18% (second), Auburn 13% (15th), Oklahoma 9% (first), Missouri 5% (25th)
Odds of a Big Ten team going 10-2 or better: Penn State 82% (SOS rank: 29th), Ohio State 77% (21st), Oregon 73% (32nd), Michigan 62% (38th), Illinois 29% (40th), Nebraska 13% (35th), USC 10% (20th), Indiana 9% (31st)
With a particularly weak nonconference schedule and a particularly good team, Penn State might be in the driver’s seat in terms of playoff qualification, while Ohio State, Oregon, Alabama, Michigan and Georgia are all over 60% likely to finish the regular season with two or fewer losses.
Odds of a Big 12 or ACC team (or Notre Dame) going 11-1 or better: Notre Dame 52% (SOS rank: 44th), Clemson 37% (34th), Miami 23% (36th), Kansas State 17% (57th), BYU 7% (64th), Texas Tech 7% (62nd), SMU 6% (45th), Arizona State 5% (61st)
Odds of a Group of 5 team going 11-1 or better: Boise State 37% (SOS rank: 84th), Liberty 17% (136th), Toledo 11% (133rd), Memphis 8% (121st), James Madison 7% (104th)
Notre Dame starts the season with games against Miami and Texas A&M, and while the rest of the schedule features plenty of solid opponents (five are projected between 30th and 47th), if the Irish are 2-0 out of the gates, they’re staring a second straight CFP appearance in the face.
Updated returning production rankings
With updated SP+ projections come updated returning production figures. A reminder: While returning production doesn’t correlate with pure quality, it does correlate well with improvement and regression, particularly at the extremes.
(Note: The production of incoming transfers is mashed into both the numerator and denominator of the returning production formula — so if you lose your starting quarterback but bring in someone else’s from the portal, your returning yardage is probably somewhere around 50%. The production of transfers from schools below the FBS level get half-credit.)
As was the case in February, Clemson leads the way here. And with the way that talent trickles upward in the transfer portal era, it’s probably not a surprise that nine of the top 10 teams in returning production (and 22 of the top 26) are power-conference teams. The P4 boasts 59.6% returning production overall, while the G5 is at 46.8%. That’s a pretty massive gap, one that isn’t likely to shrink anytime soon.
Opinion by: Ahmad Shadid of O.xyz
Semiconductors scored a rare exemption from US President Donald Trump’s aggressive reciprocal tariffs, but the relief is symbolic at best. Most semiconductors enter the US embedded in servers, GPUs, laptops, and smartphones.
The finished goods remain heavily tariffed, some with duties reaching up to 49%. The exemption looks good politically but delivers little practical benefit. Nvidia’s DGX systems, crucial for training advanced AI models, do not fall under the exempted HTS codes. Nvidia could pay effective tariffs nearing 40% on these vital components. Such costs threaten to stall critical AI infrastructure projects across the country.
Semiconductor tariffs may compromise the goal of the CHIPS Act. The act promised tens of billions of dollars in subsidies to support domestic chip manufacturing. Yet advanced lithography machines — key equipment from countries like the Netherlands and Japan — face 20%–24% tariffs. Ironically, tariffs designed to boost American production increase the cost of essential manufacturing equipment.
The effect of new tariffs is already slowing progress in critical supply chains — just as generative AI and large language models are gaining momentum across sectors like finance and defense. Any delays or cost increases now could blunt America’s technological advantage.
Indirect costs undermine exemptions for AI
Modern semiconductor supply chains are global and highly integrated. An exemption on raw silicon means nothing when servers, GPUs and other finished products face steep tariffs. Tariffs indirectly inflate costs, eliminating any competitive advantage from domestic manufacturing.
Indirect tariff costs hit high-end systems disproportionately hard. The effect ripples through AI model training, data center expansions and major infrastructure projects, significantly slowing the industry’s momentum.
Tariff impasse halts investment
So far, it’s clear that the US president’s tariff plan didn’t follow any conventional economic trends or calculated strategy. The uncertain tariff situation stalls investment decisions across the technology sector. Companies need predictable costs to justify large capital expenditures. Ongoing tariff volatility prevents them from committing resources to new data centers and manufacturing lines.
This mirrors the supply chain chaos of 2020. At that time, uncertainty caused massive order cancellations and slowed industry recovery for years. If tariff ambiguity continues, we could see similar waves of cancellations in 2025. This would further compound existing inventory and revenue issues in the semiconductor sector.
Domestic production is not optimal
The border argument for these tariffs is that they’re meant to boost domestic production. They do little, however, to encourage genuine domestic semiconductor production. Despite subsidies under the CHIPS Act, most US semiconductor companies still rely on international foundries for manufacturing. Instead, they face increased equipment and operational costs.
Recent: How trade wars impact stocks and crypto
The idea that tariffs promote domestic production ignores the reality of global semiconductor manufacturing. Costs rise across the board, putting American companies at a disadvantage rather than offering protection.
AI projects face heightened risk
The blockchain and crypto sectors, particularly AI-driven projects, also feel the pinch. Projects depend heavily on GPUs and high-performance servers for mining, validating transactions and running decentralized AI computations. Increased hardware costs directly affect profitability and growth, potentially stalling innovation in blockchain applications.
AI developments have just started to pick up the pace in the blockchain and Web3 space. The industry saw increased interest from investors and VCs just a year ago. So, they are still on tighter budgets. Elevated costs can, however, lead to stagnation. We might see innovators and developers exiting the market. The ripple effect extends beyond the general technology sector and could threaten future digital economies.
Moreover, these cost pressures disproportionately affect startups and smaller tech firms. Industry giants can absorb additional expenses, but innovative, smaller players face existential threats. This dynamic risks stifling innovation at the grassroots level, harming the entire tech ecosystem.
What to expect
Semiconductors have momentarily escaped direct tariffs, but the exemption provides little benefit. Tariffs continue to hit finished products, driving up indirect costs across the industry. Instead of boosting domestic manufacturing, these tariffs create economic paralysis, stall critical infrastructure projects, and threaten America’s lead in AI innovation. Policymakers must acknowledge these realities and adjust their approach before irreversible damage is done to the nation’s technological future.
Opinion by: Ahmad Shadid of O.xyz.
This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.
The economy will have to be “strong enough” for the government to U-turn on winter fuel payment cuts, the business secretary has said.
Jonathan Reynolds, talking to Beth Rigby on the Electoral Dysfunction podcast, also said the public would have to “wait for the actual budget” to make an announcement on it.
Sir Keir Starmer said on Wednesday he would ease the cut to the winter fuel payment, which has been removed from more than 10 million pensioners this winter after it became means-tested.
He and his ministers had insisted they would stick to their guns on the policy, even just hours before Sir Keir revealed his change of heart at Prime Minister’s Questions.
But Mr Reynolds revealed there is more at play to be able to change the policy.
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Winter fuel payment cuts to be reversed
“The economy has got to be strong enough to give you the capacity to make the kind of decisions people want us to see,” he said.
“We want people to know we’re listening.
“All the prime minister has said is ‘look, he’s listening, he’s aware of it.
“He wants a strong economy to be able to deliver for people.
“You’d have to wait for the actual budget to do that.”
Read more:
Gordon Brown suggests people on top income tax rate should be excluded from winter fuel
Chancellor Rachel Reeves has committed to just one major fiscal event a year, meaning just one annual budget in the autumn.
Autumn budgets normally take place in October, with the last one at the end of the month.
If this year’s budget is around the same date it will leave little time for the extra winter fuel payments to be made as they are paid between November and December.
You can listen to the full interview on tomorrow’s Electoral Dysfunction podcast
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