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Cal Poly

Also known as: Cal Poly Mustangs
Program History

2022 Team Stats (2 games)

65.0
PPG
67.5
Opp
-6.0
Margin
46.2%
FG%
29.4%
3P%
73.3%
FT%
32.5
RPG
10.0
APG
14.5
TO
74.1
Pace

Model Outputs

2021-2022
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 → 1008 (#274) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 927 (#611) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +115 elo More → 1152 (#22) HCA +115 elo
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +115 elo More → 870 (#629) HCA +115 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.7 More → +14.7 (#328) HCA +2.7
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.4 More → +16.1 (#112) HCA +2.4
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.4 More → +1.8 (#326) HCA +2.4
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.206 (#106) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -8.4 More → 0.282 (#187) NetEff -8.4
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -20.9 More → 0.082 (#111) AdjNet -20.9
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -21.1 More → 0.080 (#111) AdjNet -21.1
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 71.7 | AdjD 66.0 More → 0.626 (#96) AdjO 71.7 | AdjD 66.0
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.0 | AdjD 67.3 More → 0.403 (#566) AdjO 63.0 | AdjD 67.3
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 → 0.816 (#105) Blend of Elo, BT, Margin, PythLog, PtsOD
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 → 0.457 (#345) 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 → 0.799 (#98) 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 → 0.427 (#368) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 110 | GP 31 More → 1262 (#36) RD 110 | GP 31
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 147 | GP 26 More → 822 (#601) RD 147 | GP 26

2022 Schedule & Results

2022 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%
J. Davison J. Davison G 1 34.0 17.0 5.0 3.0 1.0 1.0 2.0 15.0 10.0 -17 -2.4 -3.6 46.7 40.0 50.0 0.37 53.5 53.3
A. Koroma A. Koroma - 26 27.0 13.8 5.6 0.5 0.7 0.9 2.4 2.0 17.0 -83 -3.0 -4.4 47.2 9.1 38.5 -0.17 305.7 48.1
T. Taylor T. Taylor - 3 33.7 13.7 7.3 1.3 0.3 0.3 1.3 2.3 19.3 -72 -2.7 -3.6 57.1 50.0 66.7 0.32 212.7 64.3
C. Welp C. Welp F 2 24.5 11.0 2.5 1.5 1.0 0.5 1.0 3.5 12.0 46 1.8 2.7 42.9 0.0 100.0 0.41 125.6 42.9
C. Pierce C. Pierce - 26 30.3 9.3 3.8 4.2 0.7 0.0 3.2 2.0 12.8 -55 -2.0 -2.8 40.4 5.6 85.0 0.48 198.2 41.3
C. Hunter C. Hunter - 1 15.0 9.0 3.0 1.0 0.0 0.0 1.0 0.0 12.0 -140 -4.7 -5.9 0 0 0 0.9 0 0
I. Lee I. Lee G 2 26.5 6.5 4.5 0.5 1.0 0.0 1.5 2.0 9.0 95 3.8 8.7 75.0 66.7 0.0 1.27 146.4 100.0
Kobe Sanders Kobe Sanders - 26 24.6 6.3 2.3 1.8 0.6 0.2 1.8 1.3 8.2 -127 -4.7 -7.7 38.2 40.9 80.0 -0.7 212.2 51.5
Brantly Stevenson Brantly Stevenson G 4 29.5 6.0 4.2 2.5 1.5 0.5 2.0 5.5 7.2 -104 -4.2 -5.7 40.9 14.3 33.3 -0.45 51.5 43.2
J. Franklin J. Franklin - 26 21.2 4.3 3.4 0.7 0.4 0.2 1.1 1.1 6.9 -128 -4.6 -8.3 35.7 35.3 33.3 0.85 184.4 46.4
H. Ruck H. Ruck - 1 3.0 3.0 2.0 0.0 0.0 0.0 0.0 2.0 3.0 - - - 50.0 0 100.0 - 61.5 50.0
T. Jaakkola T. Jaakkola - 26 9.9 2.5 1.7 0.2 0.2 0.2 0.6 0.3 3.9 -70 -2.5 -9.6 12.5 0 87.5 -0.74 286.5 12.5
A. Kennedy A. Kennedy F 1 22.0 2.0 2.0 1.0 0.0 0.0 1.0 4.0 0.0 -8 -0.9 -3.5 25.0 0.0 0 -0.15 25.0 25.0
H. Jory H. Jory - 10 2.9 0.6 0.4 0.0 0.0 0.1 0.4 0.1 0.6 - - - 0.0 0 0 - 300.0 0.0
N. Carlson N. Carlson - 4 2.2 0.5 0.0 0.0 0.2 0.0 0.0 0.0 0.8 - - - 0 0 0 - 0 0
K. Colvin K. Colvin F 4 10.0 0.5 2.2 0.0 0.2 0.0 1.2 0.2 1.5 -78 -3.2 -6.1 0.0 0 0 -0.21 100.0 0.0
M. Dhal M. Dhal - 2 3.0 0.0 0.0 0.0 0.0 0.5 0.0 0.5 0.0 -17 -1.3 -14.1 0.0 0 0 -0.1 0.0 0.0
D. Esparza D. Esparza C 2 2.0 0.0 0.5 0.0 0.5 0.0 0.0 0.0 1.0 -61 -3.8 -20.9 0 0 0 -0.88 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