College Football AI Predictions Week 8: ATS Picks & Score Predictions for Every Game

C Jackson Cowart - Betting Analyst at Covers.com
C Jackson Cowart • Betting Analyst 10+ years betting experience
Updated: Oct 22, 2026 , 01:00 PM ET

We trained ChatGPT to project the final score for every college football game in Week 8, along with ATS and Over/Under picks based on the latest odds from Kalshi.

College football AI predictions, Custom image featuring Houston's Conner Weigman (left), Wisconsin's Colton Joseph (middle), and Tennessee's DeSean Bishop (right).
Photo By - Custom image via Reuters Connect. Custom image featuring Houston's Conner Weigman (left), Wisconsin's Colton Joseph (middle), and Tennessee's DeSean Bishop (right).

Our college football AI predictions posted an 11-6 record outright last week on our featured picks and carry a winning record against the spread into Week 8, where our model is predicting a pair of key upsets in ranked conference matchups to headline our AI picks and score projections for all 52 games left on the Week 8 schedule.

Below are our featured matchups, followed by picks and score predictions for every game using the latest lines from Kalshi. We’ve compared this week’s AI picks with the Covers projections and Chris Gregory’s Week 8 ATS picks, with Indiana and Utah emerging as the two unanimous selections.

The following picks cover 17 featured matchups, including every AP Top 25 game on the remaining Week 7 schedule. Games are listed chronologically. All times are Eastern.

2026 featured picks record: SU 116–34 | ATS 79–71 | O/U 70–80 (through Week 7)

Kickoff Matchup ATS O/U Score
Oct 2412 pmCW
CALNo. 23SMU
CAL+20.5 Under54.5 SMU 33CAL 16
Oct 2412 pmFox
No. 6IUMICH
IU-7.5 Under41.5 IU 23MICH 14
Oct 2412 pmABC
No. 18LSUAUB
AUB+7.5 Under51.5 LSU 23AUB 19
Oct 2412 pmESPN
PITTNo. 1MIA
PITT+20.5 Over48.5 MIA 38PITT 18
Oct 2412 pmPeacock
RUTGNo. 24NW
NW-16.5 Under58.5 NW 37RUTG 17
Oct 2412 pmFS1
No. 8TTUCIN
CIN+10.5 Over56.5 TTU 33CIN 24
Oct 243:30 pmFox
No. 2BYUUCF
UCF+6.5 Under43.5 BYU 24UCF 18
Oct 243:30 pmFS1
No. 15IOWAMINN
IOWA-6.5 Over40.5 IOWA 25MINN 17
Oct 243:30 pmCBS
MSUNo. 9UCLA
UCLA-14.5 Over42.5 UCLA 31MSU 14
Oct 243:30 pmESPN
No. 11TENNSOCAR
TENN+2.5 Over50.5 TENN 27SOCAR 24
Oct 243:30 pmABC
TAMNo. 13ALA
ALA-13.5 Over50.5 ALA 34TAM 17
Oct 246 pmUSA Net
No. 21BSUWSU
WSU+13.5 Under52.5 BSU 30WSU 20
Oct 247:30 pmESPN2
ISUNo. 25ARIZ
ISU+10.5 Over50.5 ARIZ 30ISU 21
Oct 247:30 pmABC
No. 7MISSNo. 19TEX
MISS+3.5 Under53.5 TEX 27MISS 24
Oct 247:30 pmNBC
No. 16USCWIS
WIS+2.5 Under50.5 WIS 24USC 23
Oct 247:30 pmSEC Network
VANNo. 12UK
UK-10.5 Over51.5 UK 34VAN 20
Oct 2410:15 pmESPN
No. 14HOUNo. 10UTAH
UTAH-6.5 Over56.5 UTAH 35HOU 22

Lines courtesy of Kalshi and subject to change. ATS and O/U selections are graded against the exact published line.

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College football Week 8 AI picks vs. Covers projections and expert picks

Here is how the AI model compares with the Covers projections and Chris Gregory’s seven Week 8 picks against the spread. Each source retains its published line. Green rows and the consensus badge identify agreement on the same ATS team, even when the lines differ.

The Covers projections list Wisconsin at PK. That source-specific line is preserved here; our AI pick uses Wisconsin +2.5 at Kalshi.


College football Week 8 AI predictions

Cal vs. SMU AI prediction

Sat · Oct 24 · 12 pm ET · CW
Cal
16–33
Score prediction
No. 23SMU
KalshiWin probability based on market
CAL 10%SMU 91%
Projected marginSMU by 17
Projected total49 points
More analysis

SMU’s passing efficiency points toward a comfortable home win. The Mustangs average 9.4 yards per attempt, while Cal’s offense manages 6.7 through the air and 3.3 per rush. SMU also allows opponents to convert only 26.5% of third downs, a difficult matchup for a Bears team coming off a 41–7 loss to Wake Forest. The model gives SMU a 33–16 victory, but that 17-point margin leaves Cal inside +20.5. The Bears can cover without matching SMU’s offensive ceiling if they avoid short fields and make the Mustangs sustain drives. Under 54.5 follows from the 49-point projection, with Cal’s limited scoring outlook doing much of the work.

Indiana vs. Michigan AI prediction

Sat · Oct 24 · 12 pm ET · Fox
No. 6Indiana
23–14
Score prediction
Michigan
KalshiWin probability based on market
IU 73%MICH 28%
Projected marginIndiana by 9
Projected total37 points
More analysis

Indiana’s defense gives the Hoosiers a way to rebound in Ann Arbor. Indiana allows just 2.3 yards per rush and 12.9 points per game, making Michigan’s 4.2-yard rushing average a difficult foundation for an upset. The Hoosiers’ own offense averages 5.7 yards per carry and 9.9 per pass attempt, though Michigan’s defense should make those numbers harder to reproduce. Our forecast is Indiana 23, Michigan 14, producing Indiana -7.5 and Under 41.5. Indiana is also one of two unanimous ATS teams in the comparison table, although both other sources publish -6.5. The nine-point projected margin clears either number, but the extra point reduces the cushion on our selection.

LSU vs. Auburn AI prediction

Sat · Oct 24 · 12 pm ET · ABC
No. 18LSU
23–19
Score prediction
Auburn
KalshiWin probability based on market
LSU 73%AUB 29%
Projected marginLSU by 4
Projected total42 points
More analysis

Auburn’s win at Georgia makes this a demanding road assignment for LSU. The Tigers return home after a 27–24 upset, while LSU arrives off a 31–0 shutout of Mississippi State. LSU’s defense allows 2.8 yards per rush and has collected 27 sacks, giving it the tools to disrupt Auburn if the home side falls behind the chains. The model nevertheless sees a competitive game: LSU 23, Auburn 19. Auburn +7.5 provides more than a field goal of room beyond that projected margin, while Under 51.5 sits well above the 42-point forecast. Auburn sustaining its 4.7-yard rushing average would help shorten the game and keep LSU from turning defensive stops into a runaway.

Pitt vs. Miami AI prediction

Sat · Oct 24 · 12 pm ET · ESPN
Pitt
18–38
Score prediction
No. 1Miami
KalshiWin probability based on market
PITT 8%MIA 93%
Projected marginMiami by 20
Projected total56 points
More analysis

Miami’s passing attack can challenge the weaker half of Pittsburgh’s defense. Pitt allows only 2.0 yards per rush, but opponents average 7.8 yards per pass attempt. Miami averages 10.4 through the air and 48.5 points per game, so the Hurricanes have a productive alternative if running lanes are scarce. Our 38–18 Miami projection produces Pitt +20.5 and Over 48.5. The spread is a thin half-point lean, while the projected total stands 7.5 points above the line. Pitt needs enough offense to contribute to that Over; Miami’s defense allows just 2.3 yards per rush, making efficient early-down passing especially valuable for the Panthers.

Rutgers vs. Northwestern AI prediction

Sat · Oct 24 · 12 pm ET · Peacock
Rutgers
17–37
Score prediction
No. 24Northwestern
KalshiWin probability based on market
RUTG 14%NW 88%
Projected marginNorthwestern by 20
Projected total54 points
More analysis

Rutgers’ run defense gives Northwestern a clear route to control. The Scarlet Knights surrender 5.6 yards per carry and 31.8 points per game. Northwestern averages 4.8 per rush and 9.8 per pass attempt, a combination that can punish a defense whether it commits extra bodies to the box or leaves coverage exposed. The Wildcats are projected to win 37–17, covering -16.5 while staying Under 58.5. Rutgers does bring an efficient passing offense at 8.8 yards per attempt, so Northwestern cannot simply assume empty possessions. The forecast requires the Wildcats to limit that aerial production and turn their offensive balance into sustained drives, rather than a back-and-forth shootout.

Texas Tech vs. Cincinnati AI prediction

Sat · Oct 24 · 12 pm ET · FS1
No. 8Texas Tech
33–24
Score prediction
Cincinnati
KalshiWin probability based on market
TTU 80%CIN 21%
Projected marginTexas Tech by 9
Projected total57 points
More analysis

Cincinnati’s rushing attack is the key to keeping Texas Tech within reach. The Bearcats average 5.9 yards per carry, but Tech allows only 2.9. That strength-on-strength meeting matters after Cincinnati scored 42 in a loss to West Virginia and the Red Raiders put 53 on Arizona State. The model projects Texas Tech 33, Cincinnati 24, supporting Cincinnati +10.5 and Over 56.5. Tech should find opportunities against a defense allowing 8.0 yards per pass attempt, but Cincinnati needs productive early downs to keep answering. The total is only a half-point lean: a 57-point forecast does not leave much room for missed red-zone chances.

BYU vs. UCF AI prediction

Sat · Oct 24 · 3:30 pm ET · Fox
No. 2BYU
24–18
Score prediction
UCF
KalshiWin probability based on market
BYU 71%UCF 31%
Projected marginBYU by 6
Projected total42 points
More analysis

BYU’s third-down efficiency supports another win, but the road margin stays tight. The Cougars convert 56.5% of their third downs, compared with UCF’s 35.6%. Both teams can run the ball, yet BYU’s defense allows just 3.1 yards per carry and 5.5 per pass attempt, making sustained UCF possessions difficult. After beating Notre Dame 28–24, BYU gets a 24–18 win in our forecast. That makes UCF +6.5 the spread selection and Under 43.5 the total pick. The AI model joins the Covers projections on UCF, opposite Chris Gregory’s BYU selection. The cover rests on only half a point, so UCF +6 would not produce the same outright ATS pick.

Iowa vs. Minnesota AI prediction

Sat · Oct 24 · 3:30 pm ET · FS1
No. 15Iowa
25–17
Score prediction
Minnesota
KalshiWin probability based on market
IOWA 70%MINN 31%
Projected marginIowa by 8
Projected total42 points
More analysis

Iowa’s advantage on the ground can travel to Minneapolis. The Hawkeyes average 6.1 yards per rush while allowing only 2.5. Minnesota’s rushing offense manages 3.7, which puts pressure on the Gophers to find enough passing efficiency to stay out of obvious third-down situations. The projection is Iowa 25, Minnesota 17: Iowa -6.5 and Over 40.5. Minnesota allows opponents to convert just 30.9% of third downs, so Iowa’s ability to gain meaningful yardage before those situations is central to separating. The Over has a modest 1.5-point cushion, with the forecast needing Minnesota to contribute despite the difficult rushing matchup.

Michigan State vs. UCLA AI prediction

Sat · Oct 24 · 3:30 pm ET · CBS
Michigan State
14–31
Score prediction
No. 9UCLA
KalshiWin probability based on market
MSU 15%UCLA 86%
Projected marginUCLA by 17
Projected total45 points
More analysis

UCLA’s defense can keep Michigan State from sustaining enough offense. The Bruins allow 3.0 yards per rush and a 25.9% third-down conversion rate. Michigan State averages only 3.3 per carry, leaving limited room to establish the run before asking its passing game to extend drives. UCLA wins 31–14 in the model, producing UCLA -14.5 and Over 42.5. The Bruins’ own 5.6-yard rushing average provides a route to controlling possessions and field position. Michigan State needs to break that rhythm without giving up easy passing opportunities; opponents already average 7.7 yards per attempt against the Spartans. The total is the narrower selection, only 2.5 points below the projection.

Tennessee vs. South Carolina AI prediction

Sat · Oct 24 · 3:30 pm ET · ESPN
No. 11Tennessee
27–24
Score prediction
South Carolina
KalshiWin probability based on market
TENN 46%SOCAR 55%
Projected marginTennessee by 3
Projected total51 points
More analysis

Tennessee gets the upset nod after holding Alabama to 10 points. The Volunteers’ defense allows 5.5 yards per pass attempt and has generated 30 sacks. South Carolina’s rushing offense, averaging 6.0 yards per carry, offers a way to avoid those obvious passing downs and keep Tennessee’s pressure from dictating the afternoon. Our forecast favors Tennessee 27–24, giving the Volunteers +2.5 and a narrow Over 50.5. Chris Gregory also takes Tennessee, while the Covers projections favor South Carolina. The Gamecocks’ ability to run remains the main challenge to the upset call; Tennessee needs enough early-down stops to make South Carolina win through the air.

Texas A&M vs. Alabama AI prediction

Sat · Oct 24 · 3:30 pm ET · ABC
Texas A&M
17–34
Score prediction
No. 13Alabama
KalshiWin probability based on market
TAM 17%ALA 84%
Projected marginAlabama by 17
Projected total51 points
More analysis

Alabama’s passing game has an opportunity to recover from the Tennessee loss. The Crimson Tide average 9.0 yards per pass attempt, while Texas A&M’s defense has recorded just five sacks through seven games. If Alabama can protect the pocket, that leaves the Aggies needing coverage to hold up for extended stretches. The model projects Alabama 34, Texas A&M 17, supporting Alabama -13.5. A&M’s own passing offense averages 6.2 yards per attempt, so it needs productive rushing downs to avoid repeatedly chasing long conversions. Over 50.5 is much less emphatic than the spread: the 51-point score projection clears it by only half a point.

Boise State vs. Washington State AI prediction

Sat · Oct 24 · 6 pm ET · USA Net
No. 21Boise State
30–20
Score prediction
Washington State
KalshiWin probability based on market
BSU 83%WSU 18%
Projected marginBoise State by 10
Projected total50 points
More analysis

Boise State’s ground game should be productive in Pullman. The Broncos average 5.4 yards per rush against a Washington State defense allowing 4.7. Boise also converts 50.6% of third downs, while the Cougars’ offense converts only 27.8%, a gap that can tilt possession and field position toward the visitors. Our forecast still keeps Washington State inside the number: Boise State 30–20, producing Washington State +13.5 and Under 52.5. The Broncos allow 8.7 yards per pass attempt, giving the Cougars a possible way to find enough scoring chances to cover. Washington State has averaged only 5.5 itself, however, so exploiting that vulnerability is far from automatic.

Iowa State vs. Arizona AI prediction

Sat · Oct 24 · 7:30 pm ET · ESPN2
Iowa State
21–30
Score prediction
No. 25Arizona
KalshiWin probability based on market
ISU 25%ARIZ 76%
Projected marginArizona by 9
Projected total51 points
More analysis

Arizona’s passing efficiency makes the Wildcats the likely winner in Tucson. They average 9.1 yards per attempt and convert 54.8% of third downs. Iowa State allows 7.7 yards per pass attempt, so generating pressure before those routes develop is essential to keeping Arizona from repeatedly extending drives. The AI score is Arizona 30, Iowa State 21, yielding Iowa State +10.5 and Over 50.5. The Cyclones’ 5.0-yard rushing average gives them a way to stay competitive, but a 31.0% third-down conversion rate leaves little margin when early downs fail. Both selections are close to the line, particularly the total, which sits just half a point below the forecast.

Ole Miss vs. Texas AI prediction

Sat · Oct 24 · 7:30 pm ET · ABC
No. 7Ole Miss
24–27
Score prediction
No. 19Texas
KalshiWin probability based on market
MISS 42%TEX 59%
Projected marginTexas by 3
Projected total51 points
More analysis

Texas’ defense gives the Longhorns a chance to stop their slide. Texas allows 5.6 yards per pass attempt and 2.9 per rush, a strong platform against an Ole Miss offense averaging 37.5 points. The Rebels arrive after a 31–3 win over Missouri, while Texas has lost two straight, most recently 27–24 to Florida. Our 27–24 Texas forecast leaves Ole Miss +3.5 as the spread pick, alongside Under 53.5. The Ole Miss vs. Texas prediction backs Texas -3.5, making the expected margin the dividing point. A Texas win alone is not enough to settle that disagreement; the AI model has the Rebels staying within a field goal.

USC vs. Wisconsin AI prediction

Sat · Oct 24 · 7:30 pm ET · NBC
No. 16USC
23–24
Score prediction
Wisconsin
KalshiWin probability based on market
USC 59%WIS 43%
Projected marginWisconsin by 1
Projected total47 points
More analysis

Wisconsin’s pass defense is the foundation of the model’s upset call. USC averages 9.1 yards per pass attempt, but the Badgers allow only 5.7. Wisconsin also holds opponents to 3.2 yards per rush, giving it a chance to prevent the Trojans from escaping that matchup by leaning on the ground game. The projection is Wisconsin 24, USC 23, producing Wisconsin +2.5 and Under 50.5. USC’s defense allows 8.4 yards per pass attempt, offering Wisconsin a route to more offense after scoring seven at UCLA. A one-point forecast remains fragile, but the Badgers do not need to win outright to cover the published spread.

Vanderbilt vs. Kentucky AI prediction

Sat · Oct 24 · 7:30 pm ET · SEC Network
Vanderbilt
20–34
Score prediction
No. 12Kentucky
KalshiWin probability based on market
VAN 21%UK 80%
Projected marginKentucky by 14
Projected total54 points
More analysis

Kentucky’s running game can help the Wildcats build on their Oklahoma win. Kentucky averages 4.9 yards per carry against a Vanderbilt defense allowing 4.2 and 29.7 points per game. Vanderbilt’s own rushing offense averages only 3.6, increasing the importance of finding manageable passing situations. The model has Kentucky winning 34–20, covering -10.5 and going Over 51.5. Third downs are the concern for the favorite: Kentucky converts just 29.1% on offense and allows opponents to convert 47.1%. Vanderbilt can threaten the cover by extending possessions through that weakness, forcing Kentucky to sustain its scoring rather than relying on a few explosive drives.

Houston vs. Utah AI prediction

Sat · Oct 24 · 10:15 pm ET · ESPN
No. 14Houston
22–35
Score prediction
No. 10Utah
KalshiWin probability based on market
HOU 32%UTAH 69%
Projected marginUtah by 13
Projected total57 points
More analysis

Utah’s defense gives it the edge in the late Top 15 showdown. Houston averages 39.3 points per game and converts 61.4% of third downs, but Utah allows only 14.8 points and a 30.5% conversion rate. The Utes also average 5.5 yards per rush, giving their offense a dependable way to keep Houston off the field. Our forecast is Utah 35, Houston 22, producing Utah -6.5 and Over 56.5. The side joins both comparison sources, and the Houston vs. Utah prediction also favors the Utes. The total is far less decisive: 57 projected points leave only half a point above the market.


College football AI picks for every Week 8 game

Below are AI score predictions, ATS picks, Over/Under picks, kickoff times, and TV channels for all 52 remaining Week 8 games involving at least one FBS team. Tap a linked score to jump to its featured matchup breakdown. All times are Eastern.

2026 record for every game: SU 400–103 | ATS 251–250 | O/U 250–251 (through Week 7). Last week: SU 40–18 | ATS 27–31 | O/U 29–29.

Kickoff Matchup ATS O/U Score
Oct 227 pmESPNU
JMUAPP
JMU-10.5 Under55.5 JMU 35APP 18
Oct 227 pmCBSSN
LIBKENN
KENN+10.5 Under50.5 LIB 23KENN 17
Oct 227:30 pmESPN2
ECUMEM
MEM-10.5 Under53.5 MEM 33ECU 20
Oct 237 pmESPN
DUKEUVA
UVA-2.5 Under47.5 UVA 24DUKE 21
Oct 237 pmCBSSN
MASSCONN
CONN-14.5 Over49.5 CONN 37MASS 17
Oct 238:30 pmESPN2
ARMYTLSA
ARMY+1.5 Under54.5 ARMY 27TLSA 20
Oct 239 pmCW
AFAWYO
WYO+5.5 Under45.5 AFA 24WYO 19
Oct 2310:30 pmESPN
NCSTSTAN
NCST-6.5 Over55.5 NCST 34STAN 22
Oct 2412 pmCW
CALSMU
CAL+20.5 Under54.5 SMU 33CAL 16
Oct 2412 pmFox
IUMICH
IU-7.5 Under41.5 IU 23MICH 14
Oct 2412 pmABC
LSUAUB
AUB+7.5 Under51.5 LSU 23AUB 19
Oct 2412 pmESPN
PITTMIA
PITT+20.5 Over48.5 MIA 38PITT 18
Oct 2412 pmESPNU
RICEFAU
FAU-7.5 Over50.5 FAU 35RICE 23
Oct 2412 pmPeacock
RUTGNW
NW-16.5 Under58.5 NW 37RUTG 17
Oct 2412 pmFS1
TTUCIN
CIN+10.5 Over56.5 TTU 33CIN 24
Oct 2412 pmESPN2
WVUTCU
TCU-9.5 Under56.5 TCU 34WVU 20
Oct 2412 pmCBSSN
WMUTOL
TOL-3.5 Over45.5 TOL 26WMU 20
Oct 241 pmESPN+
AKRKENT
AKR+3.5 Under46.5 KENT 24AKR 21
Oct 241 pmTNT
BAYKU
KU+2.5 Under53.5 KU 27BAY 23
Oct 241 pmESPN+
M-OHCMU
M-OH-2.5 Over40.5 M-OH 23CMU 20
Oct 243 pmBTN
OREILL
ORE-9.5 Over50.5 ORE 32ILL 22
Oct 243:30 pmFox
BYUUCF
UCF+6.5 Under43.5 BYU 24UCF 18
Oct 243:30 pmACC Network
BCGT
GT-4.5 Under49.5 GT 26BC 17
Oct 243:30 pmESPN+
BGSUBUFF
BUFF-3.5 Under45.5 BUFF 24BGSU 17
Oct 243:30 pmMW+
HAWNIU
HAW-3.5 Under47.5 HAW 23NIU 17
Oct 243:30 pmFS1
IOWAMINN
IOWA-6.5 Over40.5 IOWA 25MINN 17
Oct 243:30 pmCBS
MSUUCLA
UCLA-14.5 Over42.5 UCLA 31MSU 14
Oct 243:30 pmCBSSN
UNTNAVY
UNT-2.5 Over63.5 UNT 35NAVY 30
Oct 243:30 pmSEC Network
OKLAMSST
MSST+4.5 Under46.5 MSST 24OKLA 21
Oct 243:30 pmESPN+
CSUSBALL
CSUS+14.5 Under51.5 BALL 28CSUS 23
Oct 243:30 pmESPN
TENNSOCAR
TENN+2.5 Over50.5 TENN 27SOCAR 24
Oct 243:30 pmABC
TAMALA
ALA-13.5 Over50.5 ALA 34TAM 17
Oct 243:45 pmESPN2
KSUASU
KSU-2.5 Over55.5 KSU 32ASU 26
Oct 244 pmESPNU
EMUOHIO
OHIO-11.5 Under48.5 OHIO 31EMU 17
Oct 244 pmESPN+
ULMTROY
TROY-14.5 Under50.5 TROY 35ULM 14
Oct 245 pmESPN+
ULLUSM
USM+10.5 Under52.5 ULL 31USM 21
Oct 245 pmESPN+
ODULT
ODU+11.5 Under45.5 LT 28ODU 17
Oct 245 pmMW+
SJSUNEV
NEV-6.5 Under46.5 NEV 24SJSU 17
Oct 246 pmUSA Net
BSUWSU
WSU+13.5 Under52.5 BSU 30WSU 20
Oct 246:30 pmCW
SDSUCSU
SDSU-1.5 Over62.5 SDSU 33CSU 31
Oct 247 pmFS1
COLOOKST
COLO+13.5 Under56.5 OKST 31COLO 18
Oct 247 pmESPN+
GSUARST
ARST+2.5 Under58.5 GSU 28ARST 27
Oct 247 pmESPN
VTCLEM
VT+2.5 Under49.5 VT 25CLEM 24
Oct 247:30 pmESPN2
ISUARIZ
ISU+10.5 Over50.5 ARIZ 30ISU 21
Oct 247:30 pmABC
MISSTEX
MISS+3.5 Under53.5 TEX 27MISS 24
Oct 247:30 pmACC Network
SYRUNC
SYR+9.5 Under46.5 UNC 26SYR 17
Oct 247:30 pmNBC
USCWIS
WIS+2.5 Under50.5 WIS 24USC 23
Oct 247:30 pmCBSSN
USUTXST
USU+13.5 Under60.5 TXST 34USU 23
Oct 247:30 pmSEC Network
VANUK
UK-10.5 Over51.5 UK 34VAN 20
Oct 248 pmESPNU
UTSATULN
TULN+2.5 Under51.5 TULN 27UTSA 21
Oct 2410 pmCW
NDSUUNM
UNM-4.5 Over40.5 UNM 24NDSU 17
Oct 2410:15 pmESPN
HOUUTAH
UTAH-6.5 Over56.5 UTAH 35HOU 22

The four Week 8 games completed before this edition are excluded.

More Week 8 college football picks

How our college football AI predictions work

Our college football AI predictions use a custom Bayesian score model built from historical game results, separate offensive and defensive team ratings, home-field effects, and college football scoring patterns. The model produces the scorelines shown throughout this article; the matchup analysis adds context from current team statistics and recent results.

Score projections are generated independently of market prices and are not changed to match the lines. We compare each locked score with a selected full-game spread and total to derive the ATS and Over/Under picks. This edition uses Kalshi lines for every game. The probability bars show Kalshi’s Yes asking prices, expressed as percentages, rather than the model’s own win probabilities. The two sides may not add to exactly 100%.

We publicly track every published score prediction, ATS pick, and Over/Under selection. The comparison table separately shows the Covers projections’ marked ATS selections and Chris Gregory’s expert picks, each at its original published line. A narrow difference between a forecast and a line is a lean, not a guarantee of an edge.


Odds and market lines are correct at the time of publishing and are subject to change.
Not intended for use in MA.
Affiliate Disclosure: Our team of experts has thoroughly researched and handpicked each product that appears on our website. We may receive compensation if you sign up through our links.

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C Jackson Cowart
Betting Analyst

C Jackson Cowart is a content strategy consultant for Covers with a special focus on big events and research projects. In his seven years covering sports betting as a predictive analyst, features writer, and industry reporter, he has stayed true to "process over results" while specifically targeting futures betting and news-driven markets, where he can lean on advanced metrics and an understanding of market psychology to attack value before the number moves.

An award-winning writer and editor with a decade of experience in sports media, "C-Jax" has previously worked with ESPN, Forbes, theScore, and multiple large daily newspapers. He's a proud graduate of the University of North Carolina, where he covered the Tar Heels' championship run through the 2017 NCAA men's basketball tournament. He's cashed some big tickets over the years — including Lamar Jackson to win MVP (twice) — but he's still haunted by enough second-place slips to wallpaper his home office.

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