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Virginia Tech
Virginia Tech returns 45% of last season's minutes and rates #29 on offense and #88 on defense of 365 teams. 80% range: +5.4 to +20.0.
Why we have them here
Virginia Tech's preseason projection of +12.7 (No. 45 of 365) starts from the roster: its players' ratings, weighted by projected minutes, add up to a roll-up worth +9.3, more than the +8.0 typical of teams ranked near it. Last season's rating (No. 65 at the end of 2025-26) adds +1.7, about its neighbours' +2.2; the program's level two and three seasons back and the roster's experience and shape add +1.0. A stretch at the top of the scale adds +0.4, because a straight-line calibration shrinks elite teams. It returns 45% of last season's minutes, more than teams ranked near it (33%). The projection leans most on Amani Hansberry (+6.5), Ben Hammond (+3.2) and Ethan Copeland (+2.4); the newcomer who matters most is Ethan Copeland, a transfer from Stetson, at +2.4. Its 80% range, +5.4 to +20.0, 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 43% · Transfer 52% · Other newcomer 4%
| Rank | Player | Pos | Ht | D1 yrs | Group | From | MPG | Rating | Contrib. |
|---|---|---|---|---|---|---|---|---|---|
| 12 | Amani Hansberry | F | 6-8 | 3 | Returning | Virginia Tech | 26 | +10.0 | +6.5 |
| 183 | Ben Hammond | G | 5-11 | 2 | Returning | Virginia Tech | 24 | +5.4 | +3.2 |
| 303 | Jaylen Curry | G | 6-1 | 3 | Transfer | Oklahoma State | 19 | +4.9 | +2.4 |
| 362 | Ethan Copeland | G | 6-2 | 1 | Transfer | Stetson | 23 | +4.1 | +2.4 |
| 580 | Kuol Atak | F | 6-9 | 1 | Transfer | Oklahoma | 11 | +4.1 | +1.2 |
| 649 | Tyler Johnson | G | 6-5 | 2 | Returning | Virginia Tech | 16 | +3.1 | +1.3 |
| 765 | Miles Heide | F | 6-9 | 3 | Transfer | San Diego State | 13 | +2.8 | +0.9 |
| 784 | Isaiah Elohim | G | 6-5 | 2 | Transfer | Florida Atlantic | 19 | +2.3 | +1.1 |
| 1452 | Musa Sagnia | F | 6-10 | 1 | Transfer | NC State | 8 | +0.4 | +0.1 |
| 1674 | Jailen Bedford | G | 6-4 | 3 | Returning | Virginia Tech | 16 | +0.0 | +0.0 |
| 2063 | James Caldarella | G | 6-3 | 0 | Other newcomer | 3 | -1.1 | -0.1 | |
| 2217 | Solomon Davis | F | 6-11 | 0 | Other newcomer | 3 | -1.3 | -0.1 | |
| 2277 | Eltayeb Eltayeb | G | 6-8 | 0 | Other newcomer | 3 | -1.4 | -0.1 | |
| 2496 | Sin'Cere Jones | F | 6-7 | 1 | Returning | Virginia Tech | 4 | -1.5 | -0.2 |
| 2857 | Ned Hull | G | 6-3 | 3 | Transfer | Elon | 10 | -1.2 | -0.3 |
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. | ||
|---|---|---|---|---|---|
| Tue Nov 03 | vs |  Coppin State #364 | +28.1 | 99% | |
| Thu Nov 05 | vs |  Mercer #231 | +18.4 | 93% | |
| Tue Nov 10 | N |  Iowa #33 | -1.2 | 46% | |
| Fri Nov 13 | vs |  Mount St. Mary's #204 | +16.9 | 91% | |
| Mon Nov 16 | vs |  Richmond #136 | +14.4 | 88% | |
| Fri Nov 20 | N |  Northwestern #79 | +3.3 | 60% | |
| Sun Nov 22 | N |  Oklahoma State #91 | +4.5 | 64% | |
| Fri Nov 27 | vs |  Old Dominion #297 | +20.6 | 95% | |
| Tue Dec 01 | vs |  Ole Miss #61 | +8.5 | 75% | |
| Sat Dec 05 | at |  West Virginia #48 | -6.3 | 30% | |
| Thu Dec 10 | vs |  Maryland Eastern Shore #356 | +23.9 | 97% | |
| Sun Dec 13 | vs |  Radford #241 | +18.9 | 93% | |
| Sat Dec 19 | at |  UCF #70 | -3.8 | 38% | |
| Mon Dec 21 | vs |  VMI #350 | +23.8 | 97% | |
| Wed Dec 30 | vs |  Louisville #7 | conf | -3.2 | 40% |
| Sat Jan 02 | at |  Wake Forest #76 | conf | -0.1 | 50% |
| Wed Jan 06 | at |  Notre Dame #75 | conf | +0.4 | 51% |
| Sat Jan 09 | vs |  Boston College #114 | conf | +10.0 | 79% |
| Sat Jan 16 | vs |  SMU #53 | conf | +4.3 | 63% |
| Wed Jan 20 | at |  Florida State #90 | conf | +1.3 | 54% |
| Sat Jan 23 | vs |  Miami #18 | conf | -0.7 | 48% |
| Wed Jan 27 | at |  Pittsburgh #68 | conf | -0.6 | 48% |
| Sat Jan 30 | at |  Virginia #19 | conf | -8.4 | 25% |
| Tue Feb 02 | vs |  Clemson #46 | conf | +3.4 | 61% |
| Wed Feb 10 | at |  California #115 | conf | +4.0 | 63% |
| Sat Feb 13 | at |  Stanford #69 | conf | -1.0 | 47% |
| Wed Feb 17 | vs |  NC State #36 | conf | +2.9 | 59% |
| Sat Feb 20 | at | Boston College #114 | conf | +3.9 | 62% |
| Tue Feb 23 | vs | Virginia #19 | conf | -0.6 | 48% |
| Sat Feb 27 | vs |  North Carolina #54 | conf | +4.4 | 64% |
| Wed Mar 03 | vs |  Syracuse #71 | conf | +6.3 | 69% |
| Sat Mar 06 | at |  Georgia Tech #140 | conf | +5.8 | 68% |
Projected margin is from Virginia Tech'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.