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San Francisco

Season: 2027 preview 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
-
Opp
-
Margin
43.7%
FG%
40.2%
3P%
64.7%
FT%
34.5
RPG
11.3
APG
13.8
TO
-
Est. poss./game
68.7
Adj PPG
66.6
Adj Opp PPG
#135
Scoring Rank

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 → 1100 (#108) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1001 (#175) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +102 elo More → 1009 (#160) HCA +102 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.1 More → +2.5 (#130) HCA +3.1
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.2 More → +3.6 (#117) HCA +3.2
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.483 (#175) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +3.6 More → 0.601 (#134) AdjNet +3.6
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +3.6 More → 0.602 (#135) AdjNet +3.6
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 68.7 | AdjD 66.6 More → 0.549 (#135) AdjO 68.7 | AdjD 66.6
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 68.9 | AdjD 67.4 More → 0.534 (#133) AdjO 68.9 | AdjD 67.4
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 → 0.569 (#134) 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 → 0.566 (#131) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 137 | GP 29 More → 1033 (#150) RD 137 | GP 29

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 GP PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
Cole Dickerson Cole Dickerson F 31 33.0 15.2 9.8 1.4 0.9 0.3 2.5 1.8 23.4 -45 21 -2.1 -2.9 43.6 41.2 52.6 -1.55 372.5 50.0
Cody Doolin Cody Doolin G 31 33.7 12.2 3.1 5.6 1.6 0.1 2.7 1.3 18.6 -31 21 -1.5 -2.0 56.1 33.3 70.6 1.5 389.9 62.2
De'End Parker De'End Parker G 29 27.3 11.7 3.0 2.0 0.6 0.1 1.2 1.1 15.1 -15 21 -0.7 -1.2 54.8 40.0 64.7 0.28 440.5 58.1
Tim Derksen Tim Derksen G 31 22.0 7.4 3.8 0.6 0.6 0.2 1.5 1.1 10.0 -39 21 -1.9 -3.9 41.2 37.5 72.7 -1.17 294.8 50.0
Mark Tollefsen Mark Tollefsen F 31 19.8 7.2 3.0 0.5 0.4 0.6 0.5 0.8 10.3 -26 21 -1.2 -2.8 64.0 62.5 62.5 0.08 391.0 84.0
Avry Holmes Avry Holmes G 29 19.1 6.7 1.7 0.9 0.4 0.0 1.0 0.7 7.9 -6 19 -0.3 -0.7 33.3 38.5 50.0 0.52 428.4 45.2
Chris Adams Chris Adams G 28 19.2 4.7 1.3 0.9 0.5 0.0 0.6 0.9 6.0 -39 19 -2.1 -4.4 41.7 47.6 100.0 -0.66 265.3 62.5
Tao Xu Tao Xu C 27 13.9 3.3 1.3 0.2 0.3 0.1 1.1 0.4 3.6 -15 17 -0.9 -2.7 27.3 0 75.0 -0.86 344.8 27.3
Matt Christiansen Matt Christiansen F 26 11.7 2.1 1.8 0.3 0.1 0.4 0.5 0.4 3.8 1 17 0.1 0.2 36.4 0 0 -0.33 250.0 36.4
Frank Rogers Frank Rogers F 27 9.2 1.9 1.8 0.3 0.2 0.3 0.7 0.4 3.4 -31 20 -1.6 -7.4 25.0 20.0 0.0 -1.67 201.0 29.2
Gavin Hoffmann Gavin Hoffmann G 9 5.2 0.0 0.3 0.2 0.0 0.0 0.1 0.4 0.0 - - - - 0.0 0.0 0 -0.48 0.0 0.0
Coltin Gelb Coltin 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