#105 Pittsburgh

Pittsburgh, PA - ACC
2025-2026 Schedule
Date Opponent Score
Nov 3 vs Youngstown StW 74 - 59
Nov 7 vs LongwoodW 78 - 60
Nov 10 vs Eastern MichiganW 78 - 66
Nov 13 @ West VirginiaL 71 - 49
Nov 17 vs BucknellW 84 - 50
Nov 20 (N) Central FloridaL 77 - 67
Nov 23 vs QuinnipiacL 83 - 75
Nov 28 vs #23 Ohio StW 67 - 66
Dec 2 vs Texas A&ML 81 - 73
Dec 7 vs HofstraL 80 - 73
Dec 13 @ VillanovaL 79 - 61
Dec 17 vs BinghamtonW 103 - 63
Dec 21 (N) Penn StW 80 - 46
Dec 30 @ MiamiL 76 - 69
Jan 3 vs ClemsonL 73 - 68
Jan 10 vs SyracuseL 83 - 72
Jan 14 @ Georgia TechW 89 - 66
Jan 17 vs LouisvilleL 100 - 59
Jan 21 @ Boston CollegeL 65 - 62
Jan 24 vs North Carolina StL 81 - 72
Jan 27 vs Wake ForestW 80 - 76 (OT)
Jan 31 @ ClemsonL 63 - 52
Feb 3 @ #13 VirginiaL 67 - 47
Feb 7 vs Southern MethodistL 86 - 67
Feb 10 vs #3 DukeL 70 - 54
Feb 14 @ North CarolinaL 79 - 65
Feb 21 vs Notre DameW 73 - 68
Feb 25 @ StanfordL 75 - 67
Feb 28 @ CaliforniaW 72 - 56
Mar 4 vs Florida StL 75 - 74
Mar 7 @ SyracuseW 71 - 69 (OT)
Mar 10 (N) StanfordW 64 - 63
Mar 11 (N) North Carolina StL 98 - 88
Note: Game results highlighted in green indicate that the team exceeded expectations, even if it was a loss. Games highlighted in red indicate that the team failed to meet expectations, even if it was a win.
Stats
Overall
Record13-20
vs Conference6-14
vs Top 501-9
Adj. Predicted Win %0.634 [105]
Adj. Efficiency Δ9 [91]
Strength of schedule54th
Adj. Pace64.1 [350]
Avg. Margin-1.3 [209]
Consistency345th
3-point %33.4 [204]
3-point Ratio42.9 [117]
Free Throw %67.4 [335]
OffenseDefense
Adjusted Efficiency114.6 [82]105.6 [127]
Adjusted Four Factors - Offense
ValueCorrelation
Effective FG%53.6 [98]0.84 [124]
Offensive Turnover %16.6 [219]-0.29 [263]
Offensive Rebound %34.9 [45]0.22 [266]
Free Throw Rate33.6 [217]0.36 [55]
Adjusted Four Factors - Defense
ValueCorrelation
Opponent Effective FG%51.7 [190]0.86 [76]
Defensive Turnover %16.9 [137]-0.56 [60]
Defensive Rebound %74 [37]-0.24 [247]
Opponent Free Throw Rate29.3 [57]0.19 [159]

Note: Kalman filter settling time is responsible for some of the early season variance.