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Harvard Crimson

Season: 2026 2025 2024 2023 2022 2020 2019 2018 2017 2016
Also known as: Harvard Crimson
Program History
Coach: Tommy Amaker

2013 Team Stats (7 games)

58.7
PPG
64.1
Opp
+4.2
Margin
46.0%
FG%
36.3%
3P%
71.7%
FT%
26.9
RPG
11.0
APG
12.4
TO
64.7
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 → 1265 (#190) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1344 (#119) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +147 elo More → 1073 (#76) HCA +147 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.0 More → +23.5 (#157) HCA +3.0
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More → +13.3 (#97) HCA +3.3
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.658 (#31) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -4.8 More → 0.367 (#129) NetEff -4.8
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -3.6 More → 0.398 (#76) AdjNet -3.6
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -3.7 More → 0.396 (#76) AdjNet -3.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 66.6 | AdjD 61.3 More → 0.619 (#85) AdjO 66.6 | AdjD 61.3
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 → 0.786 (#93) 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 → 0.765 (#90) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 119 | GP 30 More → 1141 (#94) RD 119 | GP 30

2013 Schedule & Results

Date Vs/At Opponent Result Score
2012-11-09 vs MIT Engineers W 69 - 54
2012-11-13 @ UMass Minutemen L 64 - 67
2012-11-16 vs Manhattan Jaspers W 79 - 45
2012-11-20 @ Saint Joseph's Hawks L 56 - 75
2012-11-27 vs Vermont Catamounts L 78 - 85
2012-12-01 vs Fordham Rams W 73 - 64
2012-12-04 @ Boston College Eagles W 79 - 63
2012-12-07 @ UConn Huskies L 49 - 57
2012-12-11 vs Boston University Terriers W 65 - 64
2012-12-22 vs Holy Cross Crusaders W 72 - 65
2012-12-29 @ California Golden Bears W 67 - 62
2012-12-31 @ Saint Mary's Gaels L 69 - 70
2013-01-05 vs Rice Owls W 92 - 62
2013-01-12 @ Dartmouth Big Green W 75 - 65
2013-01-19 @ Memphis Tigers L 50 - 60
2013-01-26 vs Dartmouth Big Green W 82 - 77
2013-02-01 vs Yale Bulldogs W 67 - 64
2013-02-02 vs Brown Bears W 89 - 82
2013-02-08 @ Cornell Big Red W 67 - 65
2013-02-10 @ Columbia Lions L 63 - 78
2013-02-15 vs Pennsylvania Quakers W 73 - 54
2013-02-16 vs Princeton Tigers W 69 - 57
2013-02-22 @ Brown Bears W 65 - 47
2013-02-23 @ Yale Bulldogs W 72 - 66
2013-03-01 @ Princeton Tigers L 53 - 58
2013-03-02 @ Pennsylvania Quakers L 72 - 75
2013-03-08 vs Columbia Lions W 56 - 51
2013-03-09 vs Cornell Big Red W 65 - 56
2013-03-21 @ New Mexico Lobos W 68 - 62
2013-03-23 @ Arizona Wildcats L 51 - 74

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%
W. Saunders W. Saunders G 30 37.3 16.2 4.2 3.5 1.8 0.4 3.0 4.5 18.5 90 3.0 3.6 51.1 50.0 74.7 0.48 140.5 52.6
S. Chambers S. Chambers G 30 37.8 12.4 2.6 5.7 1.5 0.0 3.4 3.7 15.0 141 4.9 5.9 45.5 43.6 83.9 1.04 137.8 53.2
L. Rivard L. Rivard G 30 35.4 10.3 3.6 0.8 1.0 0.0 0.7 2.8 12.3 130 4.3 5.7 42.9 43.4 80.0 1.25 167.0 62.5
C. Webster C. Webster G 30 33.6 8.4 2.9 1.6 0.9 0.4 1.6 2.9 9.7 66 2.2 2.8 34.1 33.3 28.6 0.02 134.3 46.6
S. Moundou-Missi S. Moundou-Missi F 30 20.6 7.9 5.1 0.5 0.9 0.9 1.2 2.5 11.5 94 3.1 5.4 56.0 0.0 63.6 0.6 125.1 56.0
J. Travis J. Travis F 29 16.5 6.2 3.1 0.5 0.7 0.3 1.1 1.3 8.5 42 1.4 3.4 59.5 0 82.6 -0.01 191.0 59.5
K. Smith K. Smith C 28 14.5 5.8 4.3 0.2 0.3 2.1 1.4 1.5 9.8 172 5.5 10.1 60.5 0 80.0 0.91 155.4 60.5
A. Okolie A. Okolie G 22 6.8 1.6 1.1 0.3 0.2 0.2 0.5 0.5 2.5 58 2.6 12.0 60.0 0 57.1 0.73 108.3 60.0
M. Hall M. Hall F 7 2.6 1.0 0.7 0.1 0.1 0.1 0.6 0.6 1.0 -21 -2.6 -7.3 25.0 0 50.0 -0.29 71.7 25.0
E. Cummins E. Cummins F 6 2.7 0.5 0.3 0.3 0.0 0.5 0.2 0.2 1.3 - - - 0.0 0 0 - 150.0 0.0
A. Nesbitt A. Nesbitt G 18 3.4 0.3 0.1 0.1 0.1 0.0 0.1 0.1 0.3 -1 -0.1 -0.4 50.0 0 50.0 -0.17 79.8 50.0
J. Georgatos J. Georgatos F 1 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - - - 0 0 0 - 0 0
T. Hamel T. Hamel - 1 2.0 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