Atlantic Coast Conference · men's CBB 2026-27 preview
Ratings as of 2026-10-07 · preseason, no 2026-27 games played
Rating line · rank among 364
Offense and defense are points per 100 possessions against an average D-I opponent. Net rating is the gap between them.
32 games · 18 in conference · expected wins 27.1
Each game gets a spread and a win probability from the ratings. Expected wins is the sum of those probabilities, rounded for the record.
| # | Date (ET) | Opponent | Site | Spread | Win prob. |
|---|---|---|---|---|---|
| 1 | Mon Nov 2, 6:30 PM ET | Army #349 | Home | −36.3 | >99% |
| 2 | Thu Nov 5, 8:00 PM ET | Coastal Carolina #266 | Home | −29.5 | >99% |
| 3 | Tue Nov 10, 7:00 PM ET | Michigan State #12 | Neutral at United Center State Farm Champions Classic | −5.5 | 69% |
| 4 | Fri Nov 13, 8:00 PM ET | SIU Edwardsville #255 | Home | −28.5 | >99% |
| 5 | Tue Nov 17, 7:00 PM ET | Illinois #5 Top 5 hardest | Home | −5.2 | 68% |
| 6 | Sat Nov 21, 11:00 PM ET | Washington State #165 | Neutral at Acrisure Arena Acrisure Series | −23.8 | 98% |
| 7 | Wed Nov 25, 7:00 PM ET | UConn #13 | Neutral at T-Mobile Arena | −5.8 | 70% |
| 8 | Tue Dec 1, 9:30 PM ET | Florida #4 Top 5 hardest | Away ACC/SEC Men's Challenge | −1.0 | 54% |
| 9 | Fri Dec 4, 7:00 PM ET | Harvard #178 | Home | −24.7 | 99% |
| 10 | Tue Dec 8, 9:00 PM ET | Georgia #40 | Neutral at Madison Square Garden Jimmy V Classic | −11.7 | 86% |
| 11 | Tue Dec 15, 7:00 PM ET | Campbell #163 | Home | −25.9 | 99% |
| 12 | Thu Dec 17, 8:00 PM ET | Grambling #326 | Home | −33.8 | >99% |
| 13 | Mon Dec 21, time TBA | Texas Tech #8 Top 5 hardest | Neutral at Madison Square Garden | −3.8 | 64% |
| 14 | Wed Dec 30, 7:00 PM ET | Georgia Tech #112 | Away · conference | −18.5 | 95% |
| 15 | Sat Jan 2, 2:15 PM ET | California #94 | Home · conference | −20.1 | 97% |
| 16 | Tue Jan 5, 7:00 PM ET | Syracuse #56 | Away · conference | −11.6 | 85% |
| 17 | Sat Jan 9, time TBA | Pittsburgh #83 | Home · conference | −18.1 | 95% |
| 18 | Wed Jan 13, 9:00 PM ET | Stanford #76 | Home · conference | −17.9 | 95% |
| 19 | Sat Jan 16, 7:00 PM ET | Boston College #111 | Away · conference | −17.3 | 94% |
| 20 | Wed Jan 20, 9:00 PM ET | Wake Forest #72 | Away · conference | −13.9 | 90% |
| 21 | Sat Jan 23, 2:15 PM ET | Notre Dame #74 | Home · conference | −17.5 | 94% |
| 22 | Sat Jan 30, time TBA | Clemson #19 | Away · conference | −5.3 | 69% |
| 23 | Mon Feb 1, 7:00 PM ET | Miami #24 | Home · conference | −10.2 | 82% |
| 24 | Sat Feb 6, time TBA | Virginia #22 | Away · conference | −5.8 | 70% |
| 25 | Tue Feb 9, 9:00 PM ET | SMU #50 | Away · conference | −11.2 | 84% |
| 26 | Sat Feb 13, 5:30 PM ET | North Carolina #33 | Home · conference | −12.3 | 87% |
| 27 | Tue Feb 16, 7:00 PM ET | Florida State #82 | Home · conference | −19.4 | 96% |
| 28 | Sat Feb 20, 8:00 PM ET | Gonzaga #10 Top 5 hardest | Neutral at Little Caesars Arena | −4.9 | 67% |
| 29 | Wed Feb 24, 7:00 PM ET | Louisville #9 Top 5 hardest | Away · conference | −2.5 | 59% |
| 30 | Sat Feb 27, 12:00 PM ET | NC State #29 | Home · conference | −11.3 | 85% |
| 31 | Mon Mar 1, 7:00 PM ET | Virginia #22 | Home · conference | −9.7 | 81% |
| 32 | Sat Mar 6, time TBA | North Carolina #33 | Away · conference | −8.2 | 77% |
Spread is from Duke's side: a minus sign means favored. Opponent numbers are ATO model ranks out of 364. Neutral sites carry no home edge.
15 players · sorted by projected minutes
Last season is each player's own line from the roster sheet. The projection columns are the 2026-27 per-game line from the best ball projection.
Swipe the table sideways; the player column stays put.
| Player | Pos | Ht | Class | Type | Rivals | PPG | RPG | APG | MPG | Proj MPG | Proj PTS | Proj REB | Proj AST |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Joaquim Boumtje Boumtje | C | 7-2 | FR | International | #4 | · | · | · | · | 26.0 | 9.4 | 5.3 | 1.3 |
| John Blackwell | SG | 6-5 | SR | Transfer | #220 | 19.1 | 5.1 | 2.3 | 33.8 | 21.4 | 13.2 | 3.3 | 1.7 |
| Drew Scharnowski | PF | 6-10 | JR | Transfer | · | 10.7 | 6.0 | 2.6 | 21.8 | 15.7 | 7.4 | 4.1 | 1.7 |
| Cameron Williams | PF | 7-0 | FR | Recruit | #5 | · | · | · | · | 15.7 | 5.7 | 3.2 | 0.8 |
| Cayden Boozer | PG | 6-4 | SO | Returning | #18 | 7.7 | 2.3 | 3.0 | 22.8 | 15.2 | 5.8 | 1.7 | 2.1 |
| Patrick Ngongba II | C | 6-11 | JR | Returning | #25 | 10.1 | 5.8 | 2.0 | 21.9 | 15.0 | 7.3 | 4.1 | 1.4 |
| Dame Sarr | SF | 6-8 | SO | Returning | #149 | 6.4 | 3.8 | 1.1 | 23.5 | 14.6 | 4.8 | 2.4 | 0.9 |
| Caleb Foster | PG | 6-5 | SR | Returning | #20 | 8.3 | 3.5 | 2.8 | 24.8 | 14.2 | 5.5 | 2.1 | 1.7 |
| Jacob Theodosiou | SG | 6-4 | SR | Transfer | · | 13.1 | 3.6 | 2.7 | 23.3 | 13.9 | 6.7 | 2.0 | 1.4 |
| Bryson Howard | SG | 6-4 | FR | Recruit | #28 | · | · | · | · | 12.7 | 4.8 | 1.6 | 1.0 |
| Deron Rippey Jr. | PG | 6-3 | FR | Recruit | #16 | · | · | · | · | 12.7 | 4.8 | 1.6 | 1.0 |
| Maxime Meyer | C | 7-1 | FR | Recruit | #123 | · | · | · | · | 8.1 | 2.9 | 2.0 | 0.4 |
| Brock Davis | SG | 6-5 | SR | Walk-on | · | · | · | · | · | · | · | · | · |
| Nick Arnold | PG | 5-11 | FR | Walk-on | · | · | · | · | · | · | · | · | · |
| Sebastian Wilkins | SF | 6-8 | RS FR | Returning | #60 | · | · | · | · | · | · | · | · |
PPG, RPG, APG, MPG are last season. Rivals is the recruit rank where the sheet has one. A dot means no figure.
Method · updated 2026-10-07
Ratings are net points per 100 possessions against an average D-I team, built from game results and roster information. Before games are played, the starting point is a season-ahead forecast from the roster sheet. Once the season starts, results take over.
Spreads are expected scores from each team's offense, defense and tempo, with a home edge of 2.04 points and none at neutral sites. Win probability uses a normal spread of 11 points. These are estimates of what is likely, not statements about what will happen.
Minutes and per-game lines come from a best ball projection built on last season's play, transfer and recruit information. Last-season lines and recruit ranks are facts from the roster sheet.
Every game prediction is logged before tip-off and compared with the final score. We publish where the model is close and where it misses, and we change it only when the results say to.