The SportsWire

USC

2026 · week 6 result vs Penn State

Updated Tue Oct 13, 7:55 PM CT

Next up projections

at Wisconsin

Week 8 · Fri Oct 23, 11:00 PM CT / 12:00 AM ET · Camp Randall Stadium · Wisconsin (FBS, Big Ten)

Both models favor USC.

Our call posts Monday, Oct 19, when that week's ratings are set.

Regression watch: Undersold last game: the play ran 17 points ahead of the 8-point win. In a 2022–25 study, teams undersold by more than 7 beat their season form by about 1.7 points the next game. More ›

Schedule: Played the 19th-toughest schedule in FBS so far (average opponent rating +1.4); 2nd-toughest remaining (+13.3). More ›

Opponents by our model's rating 7 played · 5 left
  • Week 1 vs San José State (-11.7)
  • Week 1 vs Fresno State (-4.3)
  • Week 2 vs Louisiana (-2.8)
  • Week 3 at Rutgers (-3.1)
  • Week 4 vs Oregon (+20.4)
  • Week 5 vs Washington (+4.2)
  • Week 6 at Penn State (+7.1)
  • Remaining:
  • Week 8 at Wisconsin (+5.3)
  • Week 9 vs Ohio State (+25.9)
  • Week 11 at Indiana (+19.1)
  • Week 12 vs Maryland (+4.9)
  • Week 13 at UCLA (+11.2)

Each opponent's rating from our model's week 7 snapshot, in points against an average FBS team; the averages are ranked among the 138 FBS teams. Played means through week 6. Experimental, like the Our model card.

Series: USC leads 7–1 · last: USC 38–21, 2024

Series history 8 meetings since 1952
  • All-time: USC leads 7–1 (8 meetings since 1952)
  • Last meeting: USC 38–21, 2024, Los Angeles Memorial Coliseum
  • Streak: none
  • At Camp Randall Stadium: first meeting at Camp Randall Stadium
  • Biggest margins: USC 38–3 (1966) · Wisconsin 23–21 (2015)
  • Since 2000: tied 1–1 (2 meetings)
SeasonResultSite
2024USC 38–21Los Angeles Memorial Coliseum
2015Wisconsin 23–21neutral site
RatingUSCWisconsin
SP+ +14.4 #21 +10.5 #34
Elo 1804 1673

Projected margin for USC · two models and the line, side by side

SP+
+1.4
USC +14.4 vs Wisconsin +10.5
avg miss 10.6
closest 47/79
Elo
+2.7
USC 1804 vs Wisconsin 1673
avg miss 12.3
closest 33/79
Line · benchmark
n/a
no pregame line
avg miss 11.1
How to read this
  • SP+ is a rating of how good a team is, in points better or worse than an average team, built from its play-by-play, so the gap between two teams' ratings is a projected margin.
  • Elo is a rating that goes up with every win and down with every loss, more for beating a strong team, less for beating a weak one. The gap between two ratings is divided by 25 to turn it into points.
  • The line is the pregame line, the margin the market expected, shown from USC's side. It is not one of the models: it is shown for comparison only, as the benchmark the models and Our call are measured against.
  • In SP+, Elo the home team gets 2.5 points (Wisconsin); the line already includes the market's own home edge. The conversion to points is approximate.
  • "avg miss 9.8" under a card is how far that model's projections have been from the actual margins this season, on average, in points. "closest 10/39" is how many of the season's 39 finished games that model came closest on (a tie counts for every tied model); the line, a benchmark, shows its average miss only. Shown once a model has 20 finished games.
  • Our call is the site's prediction: the simple average of the SP+, Elo and our model margins. The pregame line is left out of it and kept as a benchmark to measure it against. Toss-up means the average is under 3 points, Lean 3 to 7, Strong 7 or more. It is made only when all three of those models have a number, and it is scored after the game like the models.
  • Each card is one method's estimate, shown side by side; when they disagree, that is worth knowing.
  • After a game, the sentence under the score shows every model and the line against the actual margin: ✓ when a model named the winner, ✗ when it did not (the line, a benchmark, gets no mark), and Closest: the model nearest the final margin among those present, never the line (an exact tie goes to the first listed). The "closest 10/39" counts keep the accuracy report's scoring of SP+ and Elo, where a tie credits both.
  • Metrics explained: the four models and their track record ›

Efficiency matchup · season to date · USC 7 games, Wisconsin 5 games

Edge: Wisconsin wins 4 of 5

Wisconsin stops plays better, is more disruptive, has the edge on big plays and allows fewer big plays. USC moves the ball better.

USClonger bar = betterWisconsin

Run game, head to head · season to date

USC's runs work 47% of the time; Wisconsin's run defense allows 37%. Wisconsin's runs work 34% of the time; USC's run defense allows 40%.

More numbers
MeasureUSCWisconsinEdge
Off. success rate51.8%38.4%USC
Off. explosiveness1.221.53Wisconsin
Def. success rate allowed40.1%35.0%Wisconsin
Def. explosiveness allowed1.341.00Wisconsin
Havoc created12.4%15.7%Wisconsin
  • Run game, success rate: USC offense 46.5% · Wisconsin defense allows 37.3% · edge: even
  • Run game, success rate: Wisconsin offense 34.0% · USC defense allows 39.9% · edge: USC
  • Run game, PPA per play: USC offense +0.09 · Wisconsin defense allows +0.04 · edge: even
  • Run game, PPA per play: Wisconsin offense +0.22 · USC defense allows -0.02 · edge: Wisconsin
  • Success rate: how often a play does its job, gaining enough yards to keep the offense on schedule.
  • Explosiveness: how big a team's successful plays are on average; a higher number means more big gains.
  • Havoc: how often the defense blows up a play with a sack, a tackle for loss, a takeaway or a pass broken up.
  • PPA (predicted points added): how many points an average play is worth to the offense; above zero is good for the offense, below zero good for the defense.

How to read this

  • Each row compares the two teams on one measure of how well they have played this season, offense and defense, using every game so far with garbage time (plays late in a decided game) left out.
  • The run game rows pair one team's rushing offense with the other's run defense. The row goes to whichever side is further from the FBS baseline this season, the offense by how far it runs above it, the defense by how much less it allows (baseline: run success rate 43%, PPA per play +0.08, the midpoint of what FBS offenses gain and FBS defenses allow, since both also play FCS teams), so two strong sides or two weak ones are judged by which is the more so. Edges within 3 points of success rate or 0.05 PPA are even. A strong run offense against a weak run defense is where a team can control the game on the ground.
  • In the five rows at the top the longer bar is the better number: bars are scaled within each row, and in the two "allowed" rows the lower number gets the longer bar.
  • Success rate is the share of plays that kept the offense on schedule (half the yards needed on first down, most of them on second, all of them on third or fourth). Explosiveness is how big the successful plays were, on average, in points. Havoc is the share of the opponent's snaps the defense wrecked: a tackle for loss, a sack, a takeaway or a pass broken up.
  • "Allowed" rows are what each defense gave up, so the lower value wins.
  • These are not adjusted for who each team has played, so a light schedule flatters a team, and early in the season they rest on very few games.
  • Metrics explained: success rate, explosiveness and havoc ›

Injuries

No injury report yet for this game. First reports usually come Wednesday.

Coverage (AI-assisted) · 22

Gathered by an AI model from public posts, not from CollegeFootballData. Not used in any number on this page. Verify against the linked sources. Beat coverage checked Tue Oct 13, 7:30 PM CT.

5 entries about games now final not shown.

Score and result

USC 31, Penn State 23W

Game page: the call before kickoff and how each model did ›

Projected: SP+ n/a · Elo -3.9 ✗ · Our model +3.1 ✓ · the line (benchmark) -1.5 · actual +8 · Closest: Our model

USC was as low as 31% and won USC was as low as 31% and won Q1 Q2 Q3 Q4 100% 50% 0% 31–23
  1. Q1 · 3rd & 10 · 59% → 87%
    No Huddle-Shotgun #14 J.Maiava pass complete short left to #17 K.Dixon-Wyatt caught at PSU00, for 10 yards to the PSU00 TOUCHDOWN, clock 11:11, 1ST DOWN #45 C.Chittenden kick attempt good (H: #35 L.Carrigan, LS: #53 L.Brown)
  2. Q1 · 2nd & 4 · 46% → 72%
    No Huddle-Shotgun #8 K.Miller rush left for 13 yards gain to the PSU00 TOUCHDOWN, clock 05:38, 1ST DOWN #45 C.Chittenden kick attempt good (H: #35 L.Carrigan, LS: #53 L.Brown)
  3. Q1 · 2nd & 11 · 50% → 75%
    J. Maiava pass to T. Hines for 11 yds, for a TD (C. Chittenden KICK)

Away at Beaver Stadium · Sat Oct 10, 6:30 PM CT / 7:30 PM ET · vs Penn State (FBS, Big Ten)

Opponent for every game-level number: Penn State (FBS, Big Ten).

Verdict

The scoreboard undersold USC: the +8 margin ran 17 points behind the +25 implied by per-play quality (PPA (expected points added per play) +0.44 vs +0.04, success rate 50% vs 38%).

The verdict compares the score with the margin the plays earned. How it is reached ›

Efficiency

Edge: USC won 4 of 4

USC moved the ball better, got more from each play, hit the bigger plays and was more disruptive.

USClonger bar = betterPenn State
More numbers

USC ran 64 plays, Penn State 65. Each number is that team's offense; Penn State's column is also what USC's defense allowed.

MeasureUSCPenn StateEdge
PPA / play+0.44+0.04USC
Total PPA+28.2+2.8USC
Success rate50.0%38.5%USC
Explosiveness1.401.20USC
Havoc created14.3%9.5%USC
  • Success rate: how often a play did its job, gaining enough yards to keep the offense on schedule.
  • Explosiveness: how big a team's successful plays were on average; a higher number means more big gains.
  • Havoc: how often the defense blew up a play with a sack, a tackle for loss, a takeaway or a pass broken up. Counted from the play-by-play, so it is approximate.
  • PPA (predicted points added): how many points an average play was worth to the offense. Total PPA adds up every play, and is what the Verdict compares with the score.

How to read this

  • The four rows at the top compare the two offenses in this game; the longer bar is the better number, scaled within each row. A number at or below zero draws no bar.
  • A check marks the better side of a row. The line above the rows counts them: it describes how the game was played, not who won it.
  • Metrics explained ›
Top performers

USC players by cumulative PPA in this game. Usage is the share of the team's plays of that type involving the player. Receiving is passing-play PPA for non-quarterbacks.

Passing

PlayerPass usagePPA/play
Jayden Maiava QB 100% +23.2 +0.68

Rushing

PlayerRush usagePPA/play
King Miller RB 66% +3.9 +0.20
Trent Mosley WR 3% +1.3 +1.35
Waymond Jordan RB 21% -0.4 -0.07

Receiving

PlayerTarget usagePPA/play
Tanook Hines WR 21% +9.1 +1.30
Trent Mosley WR 38% +7.4 +0.57
Kayden Dixon-Wyatt WR 9% +5.2 +1.74
Zach Williams WR 15% +4.8 +0.97
By play type
MeasureUSCPenn StateEdge
Rushing PPA+0.11-0.16USC
Rushing success37.9%33.3%USC
Passing PPA+0.68+0.36USC
Passing success58.8%45.5%USC
Standard downs PPA+0.35+0.05USC
Standard downs success55.6%45.5%USC
Passing downs PPA+0.66+0.02USC
Passing downs success36.8%23.8%USC

Havoc detail — USC defense: TFL 2, sacks 2, takeaways 1, breakups 4 on 63 snaps. Penn State defense: TFL 0, sacks 1, takeaways 0, breakups 5 on 63 snaps.

Drives

A scoring opportunity is a drive that reaches the opponent's 40-yard line or scores; points per opportunity is the points those drives produced divided by their number.

◀ USCPenn State ▶
  • 9Drives9
  • 9Scoring opportunities9
  • 3.4Points per opportunity2.6
  • own 23Avg. starting field positionown 33
By half

Shown because the game changed between halves: the per-play edge swung by 0.37 points a play (USC +0.12 in the first half, +0.49 in the second). Overtime counts with the second half.

USCPenn State
1st2nd1st2nd
PPA / play+0.44+0.40+0.32-0.09
Success rate44%55%41%39%
Plays34293231

Recruiting

MeasureUSCPenn State
2026 class rank165
2026 class points310.67194.39
Talent composite 899.0
#9 of 138
774.0
#26 of 138
Transfer portal · 9 in, 22 out

Arrivals (9)

PlayerFrom★Elig.Date
Jontez Williams CB Iowa State 4 Immediate Jan 4, 2026
Terrell Anderson WR NC State 4 Immediate Jan 5, 2026
Zuriah Fisher EDGE Penn State 4 Immediate Jan 12, 2026
Carrington Pierce CB Oklahoma State 3 Immediate Dec 14, 2025
Deven Bryant LB Washington 3 Immediate Jan 4, 2026
Alex VanSumeren DL Michigan State 3 Immediate Jan 6, 2026
Tucker Ashcraft TE Wisconsin 3 Immediate Jan 15, 2026
GianCarlo Rufo LB Georgetown 3 Immediate Feb 6, 2026
Lachlan Carrigan P Memphis – Immediate Jan 9, 2026

Departures (22)

PlayerTo★Elig.Date
Devan Thompkins DL Alabama 4 Immediate Jan 7, 2026
Walker Lyons TE BYU 4 Immediate Jan 9, 2026
Anthony Beavers Jr. S Wyoming 4 Immediate Jan 10, 2026
Husan Longstreet QB LSU 4 Immediate Jan 14, 2026
Micah Banuelos IOL Purdue 3 Immediate Jan 4, 2026
Prince Strachan WR West Virginia 3 Immediate Jan 5, 2026
Makai Saina IOL Purdue 3 Immediate Jan 5, 2026
Harry Dalton III RB Maryland 3 Immediate Jan 6, 2026
Carlon Jones DL Arkansas 3 Immediate Jan 6, 2026
Bryan Jackson RB Wisconsin 3 Immediate Jan 7, 2026

+12 more not shown (22 total).

2026 commits · 34
PlayerHometown★Rating
Luke Wafle EDGE Princeton, NJ 5 0.9966
Mark Bowman TE Santa Ana, CA 5 0.9863
Jaimeon Winfield DL Richardson, TX 5 0.9842
Ethan Feaster WR DeSoto, TX 4 0.9824
Elbert Hill IV CB Akron, OH 4 0.9763
Kayden Dixon-Wyatt WR Santa Ana, CA 4 0.9731
Keenyi Pepe OT Bradenton, FL 4 0.9687
Deshonne Redeaux RB Westlake Village, CA 4 0.9628
Talanoa Ili LB Kahuku, HI 4 0.9607
Vlad Dyakonov OT Folsom, CA 4 0.9593
Jonas Williams QB Frankfort, IL 4 0.9523
Shahn Alston RB Painesville, OH 4 0.9517
Tomuhini Topui DL Santa Ana, CA 4 0.9502
Simote Katoanga DL Rancho Santa Margarita, CA 4 0.9302
Brandon Lockhart CB Chatsworth, CA 4 0.9246

+19 more not shown (34 total).

Returning production

Share of last season's production returning for USC in 2026.

Unit% PPAPPAUsage
Overall59.2%305.565.7%
Passing90.9%178.795.6%
Receiving26.9%64.325.3%
Rushing78.0%62.673.2%

A figure above 100% or below 0% is expected when last season's returning players had negative PPA in that phase, since PPA can be negative.