Teams › Big Ten · Compare USC with another team
USC
USC returns 26% of last season's minutes and rates #58 on offense and #16 on defense of 365 teams. 80% range: +6.9 to +21.6.
Why we have them here
USC's preseason projection of +14.2 (No. 35 of 365) starts from the roster: its players' ratings, weighted by projected minutes, add up to a roll-up worth +6.8, less than the +8.8 typical of teams ranked near it. Last season's rating (No. 105 at the end of 2025-26) adds +0.8, less than its neighbours' +2.5; the program's level two and three seasons back and the roster's experience and shape add +2.5. A stretch at the top of the scale adds +0.3, because a straight-line calibration shrinks elite teams. It returns 26% of last season's minutes, about the same as teams ranked near it (29%). The projection leans most on Jalen Cox (+3.3), Jacob Cofie (+3.2) and KJ Lewis (+2.4); the newcomer who matters most is Jalen Cox, a transfer from Colgate, at +3.3. Its 80% range, +6.9 to +21.6, is about as wide as that of teams ranked near it.
Generated from the published projection's own terms, not written by hand. "Teams ranked near it" are the thirty nearest in the preseason order. Preseason projection frozen 2026-10-23; how the projection is built.
Roster
Returning 26% · Transfer 57% · Freshman 16% · Other newcomer 1%
| Rank | Player | Pos | Ht | D1 yrs | Group | From | MPG | Rating | Contrib. |
|---|---|---|---|---|---|---|---|---|---|
| 170 | Jacob Cofie | F | 6-10 | 2 | Returning | USC | 22 | +5.9 | +3.2 |
| 175 | Jalen Cox | G | 6-3 | 3 | Transfer | Colgate | 23 | +5.6 | +3.3 |
| 315 | KJ Lewis | G | 6-4 | 3 | Transfer | Georgetown | 21 | +4.7 | +2.4 |
| 367 | Christian Collins | F | 6-8 | 0 | Freshman | High school | 15 | +5.0 | +1.9 |
| 577 | Eric Reibe | C | 7-1 | 1 | Transfer | UConn | 9 | +4.5 | +1.1 |
| 713 | Jadis Jones | G | 6-5 | 2 | Transfer | Lindenwood | 20 | +2.5 | +1.2 |
| 931 | Rodney Rice | G | 6-5 | 4 | Returning | USC | 16 | +1.9 | +0.8 |
| 1099 | Adonis Ratliff | F | 6-11 | 0 | Freshman | High school | 13 | +1.4 | +0.4 |
| 1229 | Darius Ratliff | C | 6-11 | 0 | Freshman | High school | 3 | +2.0 | +0.1 |
| 1600 | EJ Neal Jr. | G | 6-5 | 3 | Returning | USC | 3 | +0.2 | +0.0 |
| 2071 | Aaron Hunkin-Claytor | G | 6-3 | 2 | Transfer | Hawai'i | 13 | -0.5 | -0.2 |
| 2135 | Isaac Bruns | G | 6-5 | 3 | Transfer | South Dakota | 15 | -0.5 | -0.2 |
| 2320 | Onyeka Joe-Agu | F | 6-10 | 0 | Other newcomer | 3 | -1.6 | -0.1 | |
| 2364 | Alijah Arenas | G | 6-6 | 1 | Returning | USC | 12 | -0.8 | -0.2 |
| 4031 | Joshua Hughes | F | 6-10 | 3 | Transfer | Evansville | 14 | -1.9 | -0.7 |
A player's rating is points per 100 possessions better than an average Division I player while he is on the floor. Contribution weights it by the share of a rotation slot he is projected to play, so a star on the bench and a role player who never sits both read right. Rank is among all 5,249 rated players. MPG is the projected share of a rotation slot times 40. "From" is last season's team. The bars are contribution, the player's rating times his projected share; their sum is the roll-up the projection starts from.
Schedule
| Date | Opponent | Proj. margin | Win prob. | ||
|---|---|---|---|---|---|
| Mon Nov 02 | vs |  Milwaukee #242 | +19.2 | 94% | |
| Sun Nov 08 | N |  Wichita State #62 | +3.2 | 60% | |
| Wed Nov 11 | at |  California #115 | +1.9 | 56% | |
| Sun Nov 15 | vs |  Arkansas-Pine Bluff #349 | +25.9 | 98% | |
| Thu Nov 19 | vs |  Tarleton State #257 | +20.3 | 95% | |
| Sun Nov 22 | vs |  Louisiana #294 | +20.2 | 95% | |
| Wed Nov 25 | N |  South Carolina #98 | +6.3 | 69% | |
| Thu Nov 26 | N |  Utah State #29 | -0.9 | 47% | |
| Wed Dec 02 | vs |  Washington #92 | conf | +8.6 | 75% |
| Sat Dec 05 | at |  Oregon #58 | conf | -0.3 | 49% |
| Tue Dec 08 | at |  San Diego #263 | +8.6 | 75% | |
| Sun Dec 13 | N |  Texas Tech #15 | -4.0 | 37% | |
| Sat Dec 19 | vs |  Jacksonville #253 | +18.7 | 94% | |
| Tue Dec 22 | vs |  Western Michigan #151 | +16.0 | 90% | |
| Wed Dec 30 | at |  Purdue #38 | conf | -2.9 | 41% |
| Sat Jan 02 | at |  Indiana #55 | conf | -2.0 | 44% |
| Tue Jan 05 | at |  Maryland #64 | conf | -0.4 | 49% |
| Fri Jan 08 | at |  Rutgers #102 | conf | +3.7 | 62% |
| Tue Jan 12 | vs |  Michigan State #6 | conf | -3.0 | 40% |
| Sat Jan 16 | vs |  Wisconsin #34 | conf | +2.9 | 59% |
| Sat Jan 23 | vs |  Michigan #11 | conf | -1.8 | 44% |
| Wed Jan 27 | at |  Illinois #5 | conf | -9.9 | 21% |
| Sat Jan 30 | at |  Northwestern #79 | conf | +0.9 | 53% |
| Wed Feb 03 | vs |  Iowa #33 | conf | +2.6 | 58% |
| Sat Feb 06 | vs |  Minnesota #65 | conf | +6.0 | 69% |
| Wed Feb 10 | at | Washington #92 | conf | +2.9 | 59% |
| Sat Feb 13 | vs |  UCLA #28 | conf | +1.9 | 56% |
| Sat Feb 20 | vs |  Ohio State #27 | conf | +1.8 | 56% |
| Tue Feb 23 | at |  Nebraska #12 | conf | -8.0 | 26% |
| Sat Feb 27 | vs | Oregon #58 | conf | +5.5 | 67% |
| Tue Mar 02 | vs |  Penn State #89 | conf | +8.4 | 75% |
| Sat Mar 06 | at | UCLA #28 | conf | -4.9 | 35% |
Projected margin is from USC's side, with home court where the game is not neutral (N). Games are the schedule as posted; tournaments and late additions appear as they are listed. Predictions are as of 2026-10-26 and reflect the roster as the model has it on that date.