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UT Martin Skyhawks

Also known as: UT Martin Skyhawks
Program History

2026 Team Stats (29 games)

70.0
PPG
62.8
Opp
+7.4
Margin
42.3%
FG%
30.9%
3P%
68.8%
FT%
39.3
RPG
13.4
APG
14.0
TO
79.4
Pace
64.6
AdjO
69.2
AdjD
#229
Rank

Model Outputs

2025-2026
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 β†’ 962 (#212) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More β†’ 1033 (#148) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +109 elo More β†’ 1035 (#129) HCA +109 elo
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +109 elo More β†’ 995 (#391) HCA +109 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.2 More β†’ -4.3 (#227) HCA +2.2
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.5 More β†’ +8.7 (#249) HCA +2.5
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.5 More β†’ -7.1 (#442) HCA +2.5
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More β†’ 0.633 (#94) -
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -24.9 More β†’ 0.039 (#346) NetEff -24.9
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -5.4 More β†’ 0.350 (#227) AdjNet -5.4
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -5.4 More β†’ 0.348 (#227) AdjNet -5.4
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 64.6 | AdjD 69.2 More β†’ 0.397 (#229) AdjO 64.6 | AdjD 69.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 66.2 | AdjD 62.7 More β†’ 0.579 (#141) AdjO 66.2 | AdjD 62.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 73.4 | AdjD 74.5 More β†’ 0.476 (#360) AdjO 73.4 | AdjD 74.5
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 β†’ 0.734 (#194) 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 β†’ 0.373 (#420) 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 β†’ 0.702 (#190) 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 β†’ 0.392 (#406) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 152 | GP 30 More β†’ 1085 (#156) RD 152 | GP 30
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 350 | GP 1 More β†’ 865 (#590) RD 350 | GP 1

2026 Schedule & Results

2026 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%
A. Bukumirović A. Bukumirović - 29 29.1 13.9 7.7 0.9 1.2 0.9 1.2 9.8 13.7 151 7.2 11.6 52.5 37.8 57.3 0.38 61.0 60.4
D. Lungu D. Lungu - 6 25.7 13.8 5.3 2.8 1.3 0.2 3.5 8.3 11.7 33 5.5 9.9 62.0 27.3 54.5 0.06 64.3 65.0
Matas Deniusas Matas Deniusas - 30 25.7 12.5 5.4 1.5 0.7 0.8 1.7 9.8 9.3 144 6.5 11.5 41.5 33.1 76.5 0.72 54.3 48.6
Filip Radaković Filip Radaković - 26 26.3 9.3 4.2 2.7 1.0 0.0 2.6 6.8 7.8 190 11.2 19.7 36.2 16.7 82.7 0.99 51.7 38.4
Pedro Santos Pedro Santos - 29 18.7 6.9 4.1 0.8 1.7 0.1 1.2 6.6 5.7 77 3.9 10.0 41.7 27.5 69.0 0.24 48.6 46.6
Afan Trnka Afan Trnka G 26 23.3 6.3 2.8 2.4 1.0 0.4 1.9 5.6 5.3 22 1.0 1.9 31.7 28.0 67.2 -0.6 46.7 40.7
Filip Petkovski Filip Petkovski - 27 25.9 5.5 3.0 2.5 0.8 0.1 1.9 4.5 5.4 116 5.8 9.9 41.3 31.7 56.4 0.01 53.6 52.1
Damien King Damien King - 26 14.3 4.3 2.6 1.2 0.9 0.1 0.6 3.7 4.9 73 3.8 14.0 41.1 14.6 71.8 0.12 49.9 44.2
Aj Hopkins Aj Hopkins F 27 11.7 3.9 2.1 0.4 0.4 0.3 0.3 3.3 3.5 46 2.3 13.1 36.4 36.0 72.2 0.14 54.2 51.7
L. Colceag L. Colceag - 26 13.0 3.6 2.1 0.7 0.5 0.5 0.7 3.3 3.4 65 3.1 10.2 35.3 30.0 57.1 0.23 49.3 47.6
L. Niang L. Niang F 23 9.0 3.0 2.5 0.3 0.1 0.8 0.6 2.6 3.6 30 1.4 9.1 53.3 0 50.0 -0.36 53.6 53.3
Ama Sow Ama Sow - 5 7.0 2.8 2.8 0.2 0.0 0.2 0.8 1.6 3.6 17 2.8 21.5 62.5 100.0 50.0 0.01 65.8 68.8
Ty Price Ty Price - 15 5.5 2.6 0.3 0.3 0.1 0.1 0.5 2.1 0.8 60 3.5 39.7 38.7 41.7 83.3 0.25 58.0 54.8
Vladimir Khryapa Vladimir Khryapa - 27 13.6 2.4 2.5 0.9 0.9 0.6 1.0 2.3 3.9 22 1.2 4.3 36.5 25.9 52.4 -0.24 44.3 42.1
L. Williams L. Williams G 0 - 0.0 0.0 0.0 - - - - - 90 5.3 9.7 - - - 0.07 - -
Will Hopkins Will Hopkins G 0 - 0.0 0.0 0.0 - - - - - - - - - - - - - -
Enrique Moya Enrique Moya G 0 - 0.0 0.0 0.0 - - - - - - - - - - - - - -
James Bass James Bass F 0 - 0.0 0.0 0.0 - - - - - - - - - - - - - -
Charlie King Charlie King 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