New Mexico Lobos
2023 Team Stats (22 games)
78.9
PPG
75.9
Opp
+3.3
Margin
47.5%
FG%
36.4%
3P%
74.1%
FT%
35.0
RPG
12.2
APG
11.0
TO
80.6
Pace
Model Outputs
2022-2023
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 → | 1405 (#31) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1340 (#59) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +34.7 (#63) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.441 (#69) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.549 (#142) | NetEff +1.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.301 (#87) | AdjNet -7.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.298 (#88) | AdjNet -7.4 |
2023 Schedule & Results
2023 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. Mashburn Jr.
|
G | 25 | 34.8 | 20.2 | 3.0 | 2.1 | 0.7 | 0.0 | 1.8 | 15.0 | 9.3 | 74 | 6.2 | 8.2 | 43.0 | 38.8 | 83.0 | 1.26 | 60.0 | 47.5 |
J. House
|
- | 23 | 33.1 | 17.6 | 4.0 | 4.2 | 2.9 | 0.7 | 2.1 | 11.0 | 16.2 | - | - | - | 43.1 | 35.1 | 87.8 | - | 69.2 | 49.8 |
M. Udeze
|
- | 25 | 33.0 | 16.4 | 10.1 | 1.5 | 0.7 | 0.8 | 2.2 | 8.2 | 19.1 | - | - | - | 60.3 | 0 | 58.7 | - | 76.6 | 60.3 |
Josiah Allick
|
- | 23 | 34.0 | 8.2 | 7.0 | 1.3 | 0.6 | 0.7 | 1.5 | 5.2 | 11.0 | - | - | - | 55.8 | 21.1 | 68.3 | - | 68.5 | 57.5 |
KJ Jenkins
|
- | 24 | 18.3 | 6.4 | 1.2 | 1.0 | 0.6 | 0.1 | 0.5 | 4.8 | 4.0 | - | - | - | 41.2 | 48.3 | 84.6 | - | 63.9 | 53.5 |
J. Johnson
|
G | 24 | 27.6 | 6.0 | 3.2 | 1.0 | 0.6 | 0.1 | 0.8 | 3.9 | 6.2 | 34 | 3.8 | 9.0 | 51.1 | 37.0 | 84.6 | 1.19 | 72.2 | 61.7 |
D. Dent
|
G | 25 | 18.2 | 5.4 | 2.0 | 1.7 | 0.9 | 0.6 | 1.8 | 3.3 | 5.6 | -55 | -3.9 | -5.3 | 49.4 | 6.7 | 70.6 | 0.17 | 68.4 | 50.0 |
S. Forsling
|
- | 15 | 5.4 | 0.7 | 0.9 | 0.1 | 0.2 | 0.4 | 0.4 | 0.3 | 1.5 | - | - | - | 80.0 | 0 | 0 | - | 100.0 | 80.0 |
S. Fino-A-Laself
|
- | 6 | 1.3 | 0.5 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | 0.3 | - | - | - | 50.0 | 100.0 | 0 | - | 75.0 | 75.0 |
B. Seck
|
- | 20 | 5.7 | 0.5 | 1.1 | 0.1 | 0.0 | 0.1 | 0.2 | 0.3 | 1.2 | - | - | - | 42.9 | 0 | 66.7 | - | 51.9 | 42.9 |
B. Appelhans
|
G | 2 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | -0.5 | 27 | 2.5 | 10.0 | 0.0 | 0 | 0 | 0.58 | 0.0 | 0.0 |
Q. Webb
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
J. Allen-Tovar
|
F | 1 | 7.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
M. Manzanares
|
- | 2 | 1.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | - | - | - | 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