🐻⬇️🏀

UC Irvine

Also known as: UC Irvine Anteaters
Program History

2022 Team Stats (2 games)

65.0
PPG
61.1
Opp
+5.4
Margin
39.8%
FG%
34.4%
3P%
70.8%
FT%
31.0
RPG
9.5
APG
10.0
TO
79.3
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 → 1314 (#69) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1292 (#101) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +115 elo More → 1035 (#126) HCA +115 elo
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +115 elo More → 991 (#441) HCA +115 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.7 More → +28.7 (#104) HCA +2.7
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.4 More → +10.2 (#203) HCA +2.4
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.4 More → -10.4 (#476) HCA +2.4
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.710 (#19) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -10.1 More → 0.236 (#204) NetEff -10.1
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -3.8 More → 0.393 (#78) AdjNet -3.8
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -3.8 More → 0.393 (#78) AdjNet -3.8
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 66.1 | AdjD 63.2 More → 0.566 (#165) AdjO 66.1 | AdjD 63.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 68.1 | AdjD 70.7 More → 0.442 (#485) AdjO 68.1 | AdjD 70.7
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 → 0.729 (#173) 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 → 0.321 (#451) 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 → 0.696 (#173) 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 → 0.340 (#450) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 139 | GP 23 More → 1060 (#178) RD 139 | GP 23
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 350 | GP 2 More → 866 (#545) RD 350 | GP 2

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%
C. Welp C. Welp F 2 31.0 20.5 4.5 0.5 0.5 0.5 0.5 21.5 4.5 46 1.8 2.7 39.5 22.2 100.0 0.41 45.4 41.9
DJ Davis DJ Davis - 2 26.0 16.5 1.5 1.5 1.5 0.0 1.5 10.5 9.0 48 2.0 3.6 57.1 54.5 100.0 0.75 73.9 71.4
D. Baker D. Baker - 18 26.6 11.3 2.2 1.2 0.7 0.2 1.8 1.8 11.9 93 4.9 7.6 46.9 66.7 66.7 0.91 293.0 56.2
Justin Hohn Justin Hohn - 23 22.7 8.1 2.9 2.0 1.1 0.2 1.7 1.0 11.6 59 2.4 4.1 59.1 50.0 100.0 0.66 406.5 68.2
A. Johnson A. Johnson F 2 28.0 6.5 7.0 1.0 0.0 3.5 0.5 5.0 12.5 24 1.0 1.8 50.0 0 75.0 0.25 55.3 50.0
JC Butler JC Butler - 23 21.7 6.3 2.6 1.0 0.6 0.0 1.1 0.7 8.8 -14 -0.6 -1.0 33.3 0.0 75.0 0.31 394.2 33.3
Bent Leuchten Bent Leuchten - 22 7.1 3.5 1.9 0.3 0.1 0.2 0.7 0.7 4.6 73 3.0 17.5 53.3 50.0 75.0 0.69 226.7 56.7
A. Henry A. Henry - 14 8.8 2.2 1.4 0.4 0.4 0.1 0.5 0.2 3.7 33 2.4 10.2 33.3 0.0 75.0 0.35 325.6 33.3
Ofure Ujadughele Ofure Ujadughele - 23 12.4 2.1 2.8 1.1 0.8 0.0 1.0 0.7 5.2 64 2.6 8.3 40.0 0.0 0.0 0.68 142.4 40.0
Dean Keeler Dean Keeler - 11 7.5 1.9 2.2 0.4 0.3 0.3 0.6 0.5 3.9 48 4.0 19.7 40.0 0 0 0.55 210.0 40.0
I. Lee I. Lee G 2 16.0 1.0 1.5 1.0 0.0 0.0 0.5 2.5 0.5 95 3.8 8.7 20.0 0.0 0 1.27 20.0 20.0
E. Tshimanga E. Tshimanga F 2 7.5 1.0 3.0 0.0 0.0 0.0 1.0 1.5 1.5 22 0.9 3.0 33.3 0 0.0 0.28 21.0 33.3
L. Redfield L. Redfield - 20 8.6 0.9 0.8 0.6 0.3 0.0 0.4 0.1 2.1 28 1.3 5.5 50.0 0 0 0.1 475.0 50.0
D. Tillis D. Tillis F 0 - 0.0 0.0 0.0 - - - - - - - - - - - - - -
A. McBirney-Griffin A. McBirney-Griffin F 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