Xavier
2016 Team Stats (29 games)
79.8
PPG
70.6
Opp
+9.3
Margin
45.2%
FG%
36.3%
3P%
72.4%
FT%
40.7
RPG
16.4
APG
12.7
TO
-
Est. poss./game
82.3
Adj PPG
66.4
Adj Opp PPG
#16
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 | 1424 (#9) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1348 (#6) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1119 (#39) | HCA +98 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +17.1 (#15) | HCA +2.9 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +17.5 (#11) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.825 (#24) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.944 (#17) | AdjNet +24.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.945 (#17) | AdjNet +24.7 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.809 (#16) | AdjO 82.3 | AdjD 66.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.733 (#16) | AdjO 80.5 | AdjD 69.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.866 (#16) | 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 | 0.855 (#15) | 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 | 1362 (#7) | RD 109 | GP 34 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Trevon Bluiett
|
G | 33 | 30.6 | 15.0 | 6.1 | 2.2 | 0.9 | 0.3 | 1.6 | 10.6 | 12.4 | 176 | 27 | 6.5 | 9.6 | 42.2 | 39.0 | 80.0 | -0.32 | 61.8 | 51.7 |
Edmond Sumner
|
- | 30 | 25.8 | 11.0 | 3.4 | 3.7 | 1.3 | 0.2 | 2.1 | 7.7 | 9.6 | 152 | 26 | 5.8 | 9.8 | 38.4 | 27.0 | 73.1 | -0.07 | 56.9 | 42.7 |
Myles Davis
|
G | 33 | 29.1 | 10.8 | 3.7 | 4.1 | 0.9 | 0.2 | 1.9 | 7.3 | 10.4 | 236 | 27 | 8.7 | 13.5 | 39.7 | 38.8 | 83.8 | 6.39 | 64.2 | 51.9 |
James Farr
|
F | 33 | 20.5 | 10.6 | 7.6 | 0.5 | 0.8 | 1.0 | 1.4 | 6.9 | 12.2 | 152 | 27 | 5.6 | 12.5 | 55.0 | 14.3 | 73.1 | 2.9 | 64.6 | 55.2 |
Jalen Reynolds
|
F | 33 | 19.7 | 9.9 | 6.6 | 0.7 | 0.7 | 0.6 | 1.5 | 6.5 | 10.4 | 101 | 27 | 3.7 | 8.5 | 53.2 | 33.3 | 63.8 | -0.29 | 63.3 | 53.7 |
J.P. Macura
|
G | 33 | 22.8 | 9.2 | 2.6 | 2.0 | 1.1 | 0.0 | 1.0 | 6.2 | 7.8 | 108 | 27 | 4.0 | 7.9 | 47.1 | 36.7 | 80.6 | 1.37 | 65.1 | 55.1 |
Remy Abell
|
G | 33 | 24.5 | 6.5 | 1.7 | 1.5 | 0.5 | 0.1 | 1.0 | 4.4 | 4.8 | 199 | 27 | 7.4 | 13.9 | 39.7 | 35.8 | 77.2 | 4.92 | 62.8 | 47.9 |
Sean O'Mara
|
F | 31 | 7.0 | 3.3 | 1.9 | 0.3 | 0.2 | 0.2 | 0.6 | 1.8 | 3.5 | 5 | 25 | 0.2 | 1.3 | 59.6 | 0 | 58.8 | -1.7 | 70.9 | 59.6 |
Kaiser Gates
|
F | 30 | 10.4 | 3.2 | 2.6 | 0.2 | 0.4 | 0.2 | 0.4 | 2.2 | 4.0 | 24 | 23 | 1.0 | 4.6 | 41.5 | 31.6 | 54.8 | -0.26 | 57.5 | 50.8 |
Larry Austin
|
G | 33 | 9.7 | 1.8 | 1.2 | 1.2 | 0.5 | 0.0 | 0.8 | 1.3 | 2.5 | 11 | 26 | 0.4 | 1.9 | 38.6 | 0.0 | 60.0 | -3.56 | 50.7 | 38.6 |
Makinde London
|
F | 17 | 5.4 | 1.7 | 1.2 | 0.4 | 0.3 | 0.3 | 0.5 | 1.1 | 2.3 | 19 | 14 | 1.4 | 10.3 | 47.4 | 46.7 | 50.0 | -0.46 | 67.0 | 65.8 |
Ashanti Burgess
|
G | 3 | 1.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | 0.3 | -0.3 | - | - | - | - | 0.0 | 0 | 50.0 | -1.97 | 26.6 | 0.0 |
Kevin Coker
|
F | 6 | 1.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | -0.2 | - | - | - | - | 0.0 | 0 | 0 | -1.97 | 0.0 | 0.0 |
Tim Stainbrook
|
F | 9 | 1.9 | 0.0 | 0.0 | 0.1 | 0.0 | 0.1 | 0.1 | 0.0 | 0.1 | - | - | - | - | 0 | 0 | 0 | -1.47 | 0 | 0 |
Alex Bergen
|
G | 4 | 1.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | - | 0 | 0 | 0 | -0.94 | 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