NJIT
2026 Team Stats (32 games)
66.9
PPG
73.5
Opp
-6.6
Margin
40.5%
FG%
30.4%
3P%
70.6%
FT%
34.5
RPG
10.8
APG
11.6
TO
77.5
Pace
65.0
AdjO
79.0
AdjD
#338
Rank
Model Outputs
2025-2026
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 → | 860 (#286) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 907 (#248) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1017 (#156) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -14.1 (#337) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +0.4 (#358) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.225 (#322) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.135 (#299) | NetEff -18.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.092 (#341) | AdjNet -19.8 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.088 (#341) | AdjNet -20.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.219 (#338) | AdjO 65.0 | AdjD 79.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.410 (#598) | AdjO 67.4 | AdjD 71.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.498 (#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. More → | 0.472 (#350) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 955 (#284) | RD 139 | GP 32 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S. Robinson
|
- | 29 | 27.8 | 14.9 | 3.0 | 2.2 | 1.3 | 0.1 | 2.0 | 12.4 | 7.2 | -29 | -1.5 | -3.2 | 45.4 | 24.5 | 69.4 | -0.69 | 51.6 | 47.1 |
David Bolden
|
- | 32 | 29.8 | 11.9 | 2.8 | 2.7 | 1.9 | 0.0 | 2.0 | 10.9 | 6.3 | -131 | -6.0 | -8.8 | 31.9 | 32.4 | 81.5 | -1.04 | 48.0 | 42.0 |
A. Fulton
|
- | 32 | 28.2 | 10.8 | 6.1 | 1.2 | 0.6 | 0.5 | 1.4 | 8.4 | 9.4 | -90 | -3.9 | -6.0 | 41.9 | 26.5 | 78.8 | -0.6 | 53.7 | 46.9 |
M. Ebonkoli
|
- | 21 | 26.1 | 7.3 | 5.7 | 0.6 | 0.4 | 1.0 | 1.7 | 6.1 | 7.3 | 19 | 1.9 | 3.3 | 51.6 | 0 | 52.4 | 0.33 | 52.6 | 51.6 |
J. Clayville
|
G | 15 | 18.9 | 6.4 | 1.6 | 1.4 | 0.3 | 0.1 | 1.3 | 7.5 | 1.0 | -101 | -6.7 | -14.7 | 31.0 | 29.9 | 100.0 | -0.94 | 42.0 | 41.2 |
J. Rogers
|
- | 32 | 26.7 | 5.7 | 5.3 | 2.2 | 0.9 | 0.6 | 1.5 | 4.6 | 8.6 | -108 | -4.9 | -8.0 | 47.6 | 32.8 | 62.9 | -0.54 | 55.7 | 54.1 |
Q. Duncan
|
- | 32 | 13.5 | 4.5 | 1.6 | 0.5 | 0.4 | 0.2 | 0.3 | 4.0 | 2.9 | -87 | -4.0 | -13.8 | 39.1 | 38.1 | 52.0 | -1.13 | 52.2 | 51.6 |
J. Kelly
|
- | 32 | 15.4 | 4.2 | 2.5 | 0.4 | 0.5 | 0.1 | 0.6 | 3.2 | 4.0 | -116 | -5.3 | -13.6 | 40.2 | 31.4 | 71.7 | -1.11 | 53.0 | 45.6 |
M. Arrington
|
- | 28 | 13.9 | 3.8 | 3.8 | 0.0 | 0.2 | 0.6 | 0.8 | 2.6 | 5.1 | -80 | -3.8 | -10.3 | 58.1 | 0 | 55.3 | -0.59 | 59.0 | 58.1 |
Rocco Awad
|
- | 32 | 12.9 | 3.2 | 1.2 | 0.3 | 0.5 | 0.2 | 0.6 | 3.5 | 1.3 | -90 | -4.1 | -12.0 | 30.4 | 27.1 | 76.9 | -0.58 | 42.9 | 40.6 |
C. Piggee
|
- | 18 | 5.4 | 1.8 | 0.3 | 0.4 | 0.1 | 0.0 | 0.2 | 1.7 | 0.7 | -13 | -1.0 | -8.1 | 29.0 | 32.0 | 85.7 | -0.08 | 46.9 | 41.9 |
Zack Scherler
|
- | 19 | 6.4 | 1.0 | 1.2 | 0.2 | 0.0 | 0.3 | 0.3 | 0.7 | 1.7 | -77 | -6.4 | -33.1 | 50.0 | 0 | 55.6 | -0.78 | 52.9 | 50.0 |
J. Akintolu
|
- | 19 | 5.6 | 0.7 | 0.9 | 0.0 | 0.3 | 0.0 | 0.2 | 1.1 | 0.7 | -26 | -1.9 | -18.1 | 25.0 | 13.3 | 50.0 | -0.22 | 32.2 | 30.0 |
Stefan Jimenez-Vojnic
|
C | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
AJ Altobelli
|
G | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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