Welcome back, college football fans, as we move forward in our preseason strength of schedule (PS-SOS) countdown. We started with the least-challenged or 25th most-challenged conference, the Pioneer League whose members have an average PS-SOS of 3.341. Following the PFL, we had the SWAC (24th at 3.396), the MEAC (23rd at 3.563), the Southland Conference (22nd at 3.626), the Big South/Ohio Valley Conference (21st at 3.672), the CAA (20th at 3.808), the FCS Independents (19th at 3.844), and SoCon (18th at 3.989).
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As a reminder, the PS-SOS is calculated using the GCR’s 2025 Score (a mixture of performance and strength of schedule metrics) overlaid on each Division I (D1) team’s 2026 schedule. Special formulae are used for games against non-D1 teams (DII, DIII, NAIA, Independent). Division I is made up of the FBS (teams eligible for post-season bowls) and the FCS (teams eligible for the 24-team playoff). The FBS is broken into the Core 4 (ACC, Big 12, Big Ten, SEC, Notre Dame) and the Group of 6 (American, Conference USA, MAC, Mountain West, Pac 12, Sun Belt, UCONN). Bonus adjustments are applied for away and neutral site games. Then we take each team’s mean PS-SOS to rank them from 1-266. We also separate them into their respective 2026 conferences, take the mean of the members, and that gives us our 2026 PS-SOS countdown. The scale is calibrated such that we can look at a team’s PS-SOS and convert that number to an average opponent’s win total (for that team) assuming all games are on a neutral field. The most-challenged teams will float around 10.000 while the teams playing the weakest schedules float around 3.000.
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Today we turn our attention to the 17th most-challenged conference, or the 6th most-challenged FCS conference, the 8-team United Athletic Conference (UAC). Included this year is the D1 newcomer West Florida Argonauts who played in DII last season, where they finished a strong 10-2. In the table below, (4) indicates a challenge against a Core 4 team, (G) indicates a bout against a Group of 6 foe, (F) indicates a non-conference FCS opponent, (D) indicates a match against a non-D1 enemy, and (N) indicates a neutral site game. With no further ado, we are proud to present the 2026 UAC.
| Team Conf Rank | Home Field | 2025 Record (Rank) | 2026 PS SOS (Rank) | Home Games | Away Games | Hardest | Easiest |
| Abilene Chr Wildcats (1) | Abilene, TX | 9-5 (175) | 4.78 (141) | Steph F Austin (F), Mercer (F), West Florida, C Arkansas, West Georgia, E Kentucky | Lamar (F), Texas Tech (4), Idaho (F), North Alabama, Tarleton, Austin Peay | at Texas Tech (13.98) | West Florida (2.29) |
| E Kentucky Colonels (2) | Richmond, KY | 5-7 (225) | 4.45 (151) | Chattanooga (F), Dayton (F), North Alabama, West Georgia, West Florida, C Arkansas | W Carolina (F), Jax St (G), TN Tech (F), Tarleton, Austin Peay, Abilene Chr | at Jax St (8.74) | West Florida (2.29) |
| West Georgia Wolves (3) | Carrolton, GA | 8-3 (153) | 4.20 (167) | Chattanooga (F), Fort Valley St (D), Austin Peay, Tarleton, North Alabama, West Florida | Kennesaw St (G), Arkansas St (G), E Tenn St (F), E Kentucky, Abilene Chr, C Arkansas | at Kennesaw St (9.74) | Fort Valley St (0.08) |
| Austin Peay Governors (4) | Clarksville, TN | 7-5 (149) | 4.17 (170) | Gardner Webb (F), Morehead St (F), UT Martin (F), New Haven (F), Tarleton, E Kentucky, Abilene Chr | Vanderbilt (4), West Florida, West Georgia, North Alabama, C Arkansas | at Vanderbilt (12.30) | UT Martin (2.66) |
| C Arkansas Bears (5) | Conway, AR | 3-9 (234) | 4.00 (183) | West Florida, C Oklahoma (D), Rio Grande (F), North Alabama, West Georgia, Austin Peay | UT Martin (F), SEMO (F), Florida St (4), Abilene Chr, Tarleton, E Kentucky | at Florida St (9.50) | C Oklahoma (0.08) |
| North Alabama Lions (6) | Florence, AL | 2-10 (237) | 3.80 (207) | Alcorn St (F), W Illinois (F), Abilene Chr, Austin Peay, West Florida, Tarleton | Samford (NF), Arkansas (4), SELA (F), E Kentucky, C Arkansas, West Georgia | at Arkansas (7.58) | vs Samford (0.67) |
| Tarleton Texans (7) | Stephenville, TX | 12-2 (122) | 3.45 (239) | Prairie View (F), Merrimack (F), Chicago St (F), C Arkansas, E Kentucky, Abilene Chr | Bowling Green (G), McNeese (F), Austin Peay, West Georgia, West Florida, North Alabama | at Bowling Green (6.62) | Chicago St (0.00) |
| West Florida Argonauts (8) | Pensacola, FL | 10-2 (N/A) | 3.26 (253) | S Illinois (F), Austin Peay, NE St (D), West Alabama (D), Tarleton | C Arkansas (F), SEMO (F), Abilene Chr, E Kentucky, North Alabama, West Georgia | Tarleton (5.72) | West Alabama (0.08) |
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That’s it for today. Tune in on Saturday for episode #657 in which we will talk about Sweet 16 in our countdown. Until then, thank you for reading (it’s why we publish), thank you for your comments and suggestions over the years (it’s how we continue to improve), and thank you for sharing our content with others (it’s how we’ve seen the significant growth over the last 12 months), JoJo and G
Hi G! Another wonderful college football season is almost upon us. Thank you for continuing to publish such wonderful works of fiction, er, I mean skillful, data driven analysis! 😉 Hoping we’ll see JoJo’s commentary from time to time again this season.
I do have a question for the GCR Swami. Have your or are you planning to incorporate AI (i.e., Claude, ChatGPT, etc.) into your planning, analysis, workflow, work product, etc?
Look forward to the 2026 season G. Thanks for the insights and analysis.
Hi Stevo, aka Keytarski,
JoJo is helping behind the scenes more this summer as she has been super busy, but she appreciates the comment. Who knows? JoJo may be posting any day now. I like her commentary too.
We have not used AI for one primary reason. We know that the prep work such as inputting schedules would be quicker with AI. Incorporating the game scores would possibly be quicker than manual input, but we would lose an aspect of the GCR that some of the other computer ranking systems don’t really have – the in-season analysis. We actually pay attention to the games every week rather than just downloading the scores. We remember key matchups and outcomes – all of which helps us in our analysis.
While we have no plans right now to use AI, we may in the future. November will be a very busy month at the GCR with key football conference races including Tuesday through Saturday daily games to go along with the opening month of both men’s and women’s basketball with daily games. October has football Tuesdays through Saturdays, most of the month, paired with 730ish basketball schedules to input.
I have never really used AI for anything before and am debating the time necessary to get AI to work the way I need it vs the manual input time. Certainly, something we could consider, especially for those long basketball schedules.
The main caveat I have on AI is that the human brain is still faster than any computer out there. AI will never take over the world, but people will willingly give up skills and knowledge just to save a few minutes. That positive feedback loop could lead us down a path on which we become overly dependent on AI because the next generation never learned how to do “x” for themselves. For example, it seems every season as we add teams to the model, we get errors. Troubleshooting is not difficult because we wrote the formulae. If AI did it for us, we would probably need AI to find and fix the problem which raises the questions, “is it correct and how do we know?”
In my old career of consulting, people are using AI to record interviews and create PowerPoint presentations or a series of 1-pager project recommendations. While saving time and reducing the tedium of discovery, at some point, one should question why expensive outside resources are needed. True insights come from doing the work. I guess we know why I have no desire to get back into that industry.
Hope this helps, G (on behalf of JoJo)