UTEP
2016 Team Stats (2 games)
85.0
PPG
82.0
Opp
+3.0
Margin
48.7%
FG%
39.3%
3P%
74.1%
FT%
31.0
RPG
13.0
APG
9.5
TO
-
Est. poss./game
72.5
Adj PPG
75.8
Adj Opp PPG
#211
Scoring Rank
Model Outputs
2015-2016
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 โ | 1032 (#152) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 959 (#204) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1010 (#154) | HCA +98 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | -3.7 (#215) | HCA +2.9 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | -2.4 (#205) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.542 (#149) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.379 (#203) | AdjNet -4.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.377 (#204) | AdjNet -4.3 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.425 (#211) | AdjO 72.5 | AdjD 75.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.473 (#189) | AdjO 74.1 | AdjD 75.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.457 (#189) | 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. More โ | 0.466 (#186) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More โ | 1006 (#165) | RD 131 | GP 32 |
2016 Schedule & Results
2016 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Lee Moore
|
G | 28 | 32.5 | 15.2 | 5.5 | 3.8 | 1.4 | 0.3 | 2.1 | 3.0 | 21.1 | 36 | 19 | 1.9 | 2.6 | 45.2 | 31.0 | 73.5 | 4.95 | 202.3 | 50.6 |
Earvin Morris
|
G | 27 | 25.4 | 13.0 | 3.5 | 1.5 | 0.8 | 0.3 | 1.6 | 3.1 | 14.4 | 5 | 19 | 0.3 | 0.5 | 53.0 | 32.1 | 67.6 | 0.73 | 176.3 | 58.4 |
Omega Harris
|
G | 22 | 31.6 | 12.6 | 2.4 | 2.3 | 1.1 | 0.0 | 1.7 | 2.0 | 14.7 | -3 | 17 | -0.2 | -0.3 | 40.0 | 41.7 | 66.7 | -0.41 | 283.9 | 51.1 |
Dominic Artis
|
G | 28 | 31.9 | 11.2 | 5.1 | 5.0 | 1.1 | 0.2 | 2.1 | 2.6 | 17.9 | -12 | 19 | -0.6 | -0.9 | 35.6 | 37.5 | 69.2 | -1.58 | 185.9 | 43.8 |
Terry Winn
|
F | 27 | 24.4 | 10.7 | 6.8 | 0.6 | 0.6 | 0.8 | 1.6 | 2.1 | 15.8 | -25 | 19 | -1.3 | -2.5 | 49.1 | 0 | 52.4 | -1.89 | 191.4 | 49.1 |
Hooper Vint
|
C | 28 | 21.7 | 9.1 | 5.0 | 0.6 | 0.2 | 1.1 | 1.6 | 1.5 | 13.0 | -19 | 19 | -1.0 | -2.1 | 51.2 | 20.0 | 66.7 | -2.91 | 267.9 | 52.4 |
Matt Willms
|
C | 1 | 13.0 | 6.0 | 4.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 9.0 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Tevin Caldwell
|
G | 23 | 11.2 | 3.0 | 2.2 | 0.6 | 0.4 | 0.1 | 0.5 | 0.3 | 5.6 | 7 | 15 | 0.5 | 1.6 | 71.4 | 0 | 100.0 | -0.11 | 375.0 | 71.4 |
Trey Touchet
|
G | 25 | 10.0 | 2.4 | 0.7 | 0.8 | 0.2 | 0.0 | 0.5 | 0.7 | 3.0 | -32 | 17 | -1.9 | -7.7 | 47.1 | 44.4 | 50.0 | -3.5 | 170.6 | 58.8 |
Victor Mbachu
|
- | 3 | 5.0 | 2.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.3 | 0.3 | 1.7 | - | - | - | - | 0.0 | 0.0 | 50.0 | - | 159.6 | 0.0 |
Paul Thomas
|
F | 18 | 10.5 | 1.8 | 2.4 | 0.4 | 0.3 | 0.3 | 0.6 | 0.4 | 4.2 | 4 | 10 | 0.4 | 2.2 | 50.0 | 0 | 33.3 | -0.72 | 155.1 | 50.0 |
Jake Flaggert
|
F | 26 | 12.7 | 1.7 | 1.1 | 0.5 | 0.2 | 0.1 | 0.3 | 0.4 | 2.9 | -17 | 17 | -1.0 | -4.1 | 18.2 | 18.2 | 0.0 | -2.17 | 196.7 | 27.3 |
Christian Romine
|
- | 13 | 3.6 | 0.9 | 0.4 | 0.0 | 0.0 | 0.0 | 0.5 | 0.1 | 0.7 | - | - | - | - | 0.0 | 0 | 0 | - | 600.0 | 0.0 |
Brodricks Jones
|
F | 13 | 7.8 | 0.8 | 1.4 | 0.2 | 0.2 | 0.6 | 0.5 | 0.1 | 2.5 | - | - | - | - | 0.0 | 0 | 0 | - | 500.0 | 0.0 |
Ivan Venegas
|
F | 6 | 3.2 | 0.8 | 1.5 | 0.2 | 0.0 | 0.2 | 0.0 | 0.0 | 2.7 | - | - | - | - | 0 | 0 | 0.0 | 0.33 | 284.1 | 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