#86 George Washington

Washington, DC - Atlantic 10
2025-2026 Schedule
Date Opponent Score
Nov 3 vs MaineW 67 - 47
Nov 8 (N) South FloridaW 99 - 95
Nov 12 vs American UniversityW 107 - 67
Nov 15 vs Old DominionW 96 - 73
Nov 19 vs Md Baltimore CountyW 89 - 52
Nov 23 (N) McNeeseL 92 - 86
Nov 24 (N) Middle TennesseeW 92 - 79
Nov 25 (N) Murray StL 96 - 95
Dec 2 @ ArmyW 84 - 70
Dec 6 vs William & MaryW 99 - 86
Dec 10 vs DelawareL 70 - 58
Dec 13 (N) #6 FloridaL 80 - 70
Dec 31 @ RichmondW 99 - 85
Jan 3 vs La SalleW 77 - 55
Jan 6 @ DaytonL 79 - 72
Jan 10 vs Loyola ChicagoW 101 - 66
Jan 14 vs DavidsonL 84 - 79
Jan 19 @ George MasonL 69 - 64
Jan 24 vs RichmondW 85 - 69
Jan 27 @ Saint LouisL 79 - 76
Jan 31 vs FordhamL 79 - 65
Feb 4 @ Saint Joseph'sL 76 - 73
Feb 7 @ DuquesneL 88 - 86
Feb 10 vs Rhode IslandW 75 - 70
Feb 13 vs George MasonW 72 - 53
Feb 17 @ Virginia CommonwealthL 89 - 75
Feb 24 @ La SalleW 104 - 77
Feb 27 vs DaytonL 68 - 66
Mar 4 vs St. BonaventureW 91 - 82 (OT)
Mar 7 @ Loyola ChicagoL 68 - 62
Mar 12 (N) FordhamW 66 - 62
Mar 13 (N) Saint LouisL 88 - 81
Mar 18 @ Utah ValleyW 79 - 78
Mar 22 @ New MexicoL 86 - 61
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
Record18-16
vs Conference9-11
vs Top 501-6
Adj. Predicted Win %0.672 [86]
Adj. Efficiency Δ9.8 [86]
Strength of schedule111th
Adj. Pace69 [126]
Avg. Margin5.7 [65]
Consistency248th
3-point %35.1 [105]
3-point Ratio47 [33]
Free Throw %72.3 [197]
OffenseDefense
Adjusted Efficiency117.1 [59]107.3 [167]
Adjusted Four Factors - Offense
ValueCorrelation
Effective FG%55.6 [54]0.83 [152]
Offensive Turnover %18.2 [300]-0.37 [197]
Offensive Rebound %36 [31]0.07 [342]
Free Throw Rate36.1 [152]0.23 [129]
Adjusted Four Factors - Defense
ValueCorrelation
Opponent Effective FG%51.4 [177]0.71 [329]
Defensive Turnover %17.1 [123]-0.66 [13]
Defensive Rebound %72.7 [85]-0.59 [13]
Opponent Free Throw Rate34.8 [187]0.48 [12]

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