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San Francisco

Season: 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017
Also known as: San Francisco Dons, San Francisco
Program History
Coach: Chris Gerlufsen

2013 Team Stats (4 games)

66.3
PPG
69.1
Opp
+0.6
Margin
43.7%
FG%
40.2%
3P%
64.7%
FT%
34.5
RPG
11.3
APG
13.8
TO
74.5
Pace

Model Outputs

2012-2013
Catalog

Output is shown as model rating with league rank in parentheses when available.

Model Output Notes
Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → 1380 (#118) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1341 (#120) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 836 (#1045) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +147 elo More → 1044 (#113) HCA +147 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.0 More → +30.2 (#85) HCA +3.0
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More → +11.8 (#118) HCA +3.3
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.334 (#86) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff +0.4 More → 0.511 (#94) NetEff +0.4
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -10.4 More → 0.232 (#92) AdjNet -10.4
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -10.7 More → 0.226 (#92) AdjNet -10.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 69.7 | AdjD 67.0 More → 0.561 (#141) AdjO 69.7 | AdjD 67.0
Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.725 (#138) Blend of Elo, BT, Margin, PythLog, PtsOD
Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.700 (#136) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 136 | GP 30 More → 1084 (#138) RD 136 | GP 30

2013 Schedule & Results

Date Vs/At Opponent Result Score
2012-11-09 @ Stanford Cardinal L 62 - 74
2012-11-13 vs Cal State East Bay Pioneers W 73 - 58
2012-11-19 @ American University Eagles W 67 - 53
2012-11-24 vs Columbia Lions W 79 - 59
2012-11-30 vs Montana Grizzlies W 78 - 68
2012-12-04 vs St. John's Red Storm W 81 - 65
2012-12-08 @ Pacific Tigers L 59 - 67
2012-12-15 @ Nevada Wolf Pack L 51 - 59
2012-12-18 vs Holy Cross Crusaders L 63 - 73
2012-12-22 vs San Diego State Aztecs L 58 - 80
2012-12-23 vs Ole Miss Rebels L 78 - 85
2012-12-25 @ East Tennessee State Buccaneers W 67 - 49
2012-12-29 vs Dominican Cal Penguins W 93 - 76
2013-01-02 @ Santa Clara Broncos L 69 - 74
2013-01-05 vs BYU Cougars L 76 - 80
2013-01-10 vs San Diego Toreros L 66 - 70
2013-01-12 @ Saint Mary's Gaels L 72 - 78
2013-01-17 vs Santa Clara Broncos L 54 - 85
2013-01-19 vs Loyola Marymount Lions W 62 - 53
2013-01-24 @ Portland Pilots W 75 - 72
2013-01-26 @ Gonzaga Bulldogs L 52 - 66
2013-01-30 vs Saint Mary's Gaels L 63 - 67
2013-02-02 @ Pepperdine Waves W 86 - 78
2013-02-09 @ BYU Cougars W 99 - 87
2013-02-14 vs Portland Pilots L 76 - 78
2013-02-16 vs Gonzaga Bulldogs L 61 - 71
2013-02-21 @ Loyola Marymount Lions W 61 - 59
2013-02-23 vs Pepperdine Waves W 64 - 58
2013-02-28 @ San Diego Toreros W 83 - 70
2013-03-07 vs Loyola Marymount Lions L 60 - 61
2013-03-14 vs Northern Kentucky Norse W 73 - 68

2013 Roster

Minutes by Position

The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.

Player Pos GP MIN PTS REB AST STL BLK TO FGA Numbers PM PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
C. Dickerson C. Dickerson F 31 33.0 15.2 9.8 1.4 0.9 0.3 2.5 1.8 23.4 40 1.6 3.9 43.6 41.2 52.6 0.36 372.5 50.0
C. Doolin C. Doolin G 31 33.7 12.2 3.1 5.6 1.6 0.1 2.7 1.3 18.6 43 1.4 1.7 56.1 33.3 70.6 0.62 389.9 62.2
D. Parker D. Parker G 29 27.3 11.7 3.0 2.0 0.6 0.1 1.2 1.1 15.1 48 1.7 2.4 54.8 40.0 64.7 0.69 440.5 58.1
T. Derksen T. Derksen G 31 22.0 7.4 3.8 0.6 0.6 0.2 1.5 1.1 10.0 21 0.7 1.4 41.2 37.5 72.7 0.37 294.8 50.0
M. Tollefsen M. Tollefsen F 31 19.8 7.2 3.0 0.5 0.4 0.6 0.5 0.8 10.3 34 1.1 2.0 64.0 62.5 62.5 0.58 391.0 84.0
A. Holmes A. Holmes G 29 19.1 6.7 1.7 0.9 0.4 0.0 1.0 0.7 7.9 37 1.3 2.4 33.3 38.5 50.0 0.51 428.4 45.2
C. Adams C. Adams G 28 19.2 4.7 1.3 0.9 0.5 0.0 0.6 0.9 6.0 90 2.6 5.2 41.7 47.6 100.0 0.24 265.3 62.5
T. Xu T. Xu C 27 13.9 3.3 1.3 0.2 0.3 0.1 1.1 0.4 3.6 -29 -1.1 -3.6 27.3 0 75.0 -0.45 344.8 27.3
M. Christiansen M. Christiansen F 26 11.7 2.1 1.8 0.3 0.1 0.4 0.5 0.4 3.8 -15 -0.8 -2.8 36.4 0 0 -0.06 250.0 36.4
F. Rogers F. Rogers F 27 9.2 1.9 1.8 0.3 0.2 0.3 0.7 0.4 3.4 32 1.1 3.8 25.0 20.0 0.0 0.36 201.0 29.2
G. Hoffmann G. Hoffmann G 9 5.2 0.0 0.3 0.2 0.0 0.0 0.1 0.4 0.0 2 0.2 1.6 0.0 0.0 0 0.13 0.0 0.0
C. Gelb C. Gelb - 2 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - - - 0 0 0 - 0 0

Numbers/Game vs RAPM

X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.

Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG