#10 Alabama

Tuscaloosa, AL - SEC
2025-2026 Schedule
Date Opponent Score
Nov 3 vs North DakotaW 91 - 62
Nov 8 @ #12 St. John'sW 103 - 96
Nov 13 vs #7 PurdueL 87 - 80
Nov 19 (N) #8 IllinoisW 90 - 86
Nov 24 (N) #22 GonzagaL 95 - 85
Nov 25 (N) UNLVW 115 - 76
Nov 26 (N) MarylandW 105 - 72
Dec 3 vs ClemsonW 90 - 84
Dec 7 vs Texas San AntonioW 97 - 55
Dec 13 (N) #1 ArizonaL 96 - 75
Dec 17 vs South FloridaW 104 - 93
Dec 21 (N) Kennesaw StW 92 - 81
Dec 29 vs YaleW 102 - 78
Jan 3 vs KentuckyW 89 - 74
Jan 7 @ #15 VanderbiltL 96 - 90
Jan 10 vs TexasL 92 - 88
Jan 13 @ Mississippi StW 97 - 82
Jan 17 @ OklahomaW 83 - 81
Jan 24 vs #20 TennesseeL 79 - 73
Jan 27 vs MissouriW 90 - 64
Feb 1 @ #6 FloridaL 100 - 77
Feb 4 vs Texas A&MW 100 - 97
Feb 7 @ AuburnW 96 - 92
Feb 11 @ MississippiW 93 - 74
Feb 14 vs South CarolinaW 89 - 75
Feb 18 vs #19 ArkansasW 117 - 115 (2 OT)
Feb 21 @ LSUW 90 - 83
Feb 25 vs Mississippi StW 100 - 75
Feb 28 @ #20 TennesseeW 71 - 69
Mar 3 @ GeorgiaL 98 - 88
Mar 7 vs AuburnW 96 - 84
Mar 13 (N) MississippiL 80 - 79
Mar 20 (N) HofstraW 90 - 70
Mar 22 (N) #16 Texas TechW 90 - 65
Mar 27 (N) #2 MichiganL 90 - 77
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
Record25-10
vs Conference13-6
vs Top 5011-8
Adj. Predicted Win %0.913 [10]
Adj. Efficiency Δ28.5 [11]
Strength of schedule4th
Adj. Pace72.7 [11]
Avg. Margin8.5 [34]
Consistency215th
3-point %35.8 [68]
3-point Ratio54.1 [1]
Free Throw %76.7 [38]
OffenseDefense
Adjusted Efficiency129.4 [5]100.9 [56]
Adjusted Four Factors - Offense
ValueCorrelation
Effective FG%58.8 [12]0.64 [359]
Offensive Turnover %12.9 [17]-0.17 [313]
Offensive Rebound %34.1 [65]0.7 [2]
Free Throw Rate34.8 [186]0.09 [260]
Adjusted Four Factors - Defense
ValueCorrelation
Opponent Effective FG%46.3 [19]0.75 [299]
Defensive Turnover %14.1 [322]-0.47 [127]
Defensive Rebound %71.1 [137]-0.55 [29]
Opponent Free Throw Rate28.6 [42]0.21 [141]

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