Davidson
2014 Team Stats (6 games)
72.5
PPG
81.5
Opp
-9.0
Margin
43.6%
FG%
40.9%
3P%
65.3%
FT%
30.2
RPG
12.5
APG
13.8
TO
-
Est. poss./game
75.3
Adj PPG
73.5
Adj Opp PPG
#137
Scoring Rank
Model Outputs
2013-2014
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 | 1134 (#74) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1038 (#141) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1076 (#68) | HCA +92 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +1.7 (#145) | HCA +2.8 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +5.0 (#102) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.666 (#79) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.591 (#134) | AdjNet +3.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.592 (#134) | AdjNet +3.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.543 (#137) | AdjO 75.3 | AdjD 73.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.641 (#51) | AdjO 75.6 | AdjD 69.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.604 (#114) | 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 | 0.623 (#104) | 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 | 1041 (#142) | RD 126 | GP 32 |
2014 Schedule & Results
2014 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
De'Mon Brooks
|
F | 23 | 26.9 | 18.6 | 6.9 | 1.3 | 0.7 | 0.8 | 2.4 | 4.1 | 21.8 | 137 | 19 | 7.2 | 12.1 | 45.7 | 37.5 | 68.4 | 6.41 | 179.7 | 48.9 |
Brian Sullivan
|
G | 26 | 31.3 | 13.9 | 2.4 | 2.2 | 0.8 | 0.0 | 1.4 | 4.7 | 13.2 | 21 | 24 | 0.9 | 1.3 | 37.7 | 39.0 | 65.0 | -1.4 | 138.0 | 50.0 |
Tyler Kalinoski
|
G | 26 | 34.4 | 11.5 | 4.9 | 3.4 | 1.3 | 0.3 | 1.5 | 2.4 | 17.5 | 60 | 24 | 2.5 | 3.3 | 52.4 | 58.8 | 65.0 | 1.25 | 207.5 | 68.3 |
Tom Droney
|
G | 26 | 30.2 | 9.2 | 3.7 | 3.4 | 0.7 | 0.1 | 2.3 | 2.9 | 12.0 | 25 | 23 | 1.1 | 1.5 | 40.8 | 34.5 | 68.8 | -1.68 | 133.2 | 47.4 |
Chris Czerapowicz
|
G | 26 | 24.7 | 8.6 | 4.0 | 0.8 | 0.4 | 0.3 | 0.8 | 2.9 | 10.4 | 22 | 24 | 0.9 | 1.6 | 42.7 | 33.3 | 66.7 | -1.98 | 139.5 | 50.0 |
Jack Gibbs
|
G | 25 | 19.4 | 6.5 | 1.7 | 2.0 | 0.9 | 0.0 | 1.5 | 1.8 | 7.8 | 85 | 24 | 3.5 | 7.7 | 40.0 | 35.0 | 76.2 | 3.49 | 150.3 | 47.8 |
Jake Belford
|
F | 19 | 15.7 | 6.2 | 2.2 | 0.3 | 0.4 | 0.1 | 1.2 | 1.3 | 6.6 | 1 | 17 | 0.1 | 0.2 | 58.3 | 57.1 | 75.0 | -4.01 | 227.1 | 75.0 |
Jordan Barham
|
G | 26 | 11.9 | 5.3 | 2.8 | 0.3 | 0.4 | 0.0 | 0.5 | 1.3 | 7.2 | -42 | 24 | -1.8 | -6.3 | 51.5 | 0.0 | 42.1 | -4.73 | 166.8 | 51.5 |
Andrew McAuliffe
|
F | 24 | 9.0 | 2.0 | 1.6 | 0.3 | 0.1 | 0.1 | 0.7 | 0.6 | 2.9 | -23 | 22 | -1.0 | -3.9 | 60.0 | 0.0 | 0.0 | -0.61 | 150.1 | 60.0 |
Ali Mackay
|
F | 12 | 4.0 | 1.2 | 0.9 | 0.2 | 0.0 | 0.0 | 0.1 | 0.2 | 2.1 | -8 | 10 | -0.8 | -12.3 | 50.0 | 0.0 | 0 | -2.64 | 375.0 | 50.0 |
Connor Perkey
|
F | 5 | 2.0 | 0.8 | 0.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.4 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Ryan Ansel
|
- | 4 | 2.2 | 0.8 | 0.5 | 0.2 | 0.2 | 0.0 | 0.2 | 0.0 | 1.5 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Joe Aase
|
F | 18 | 6.3 | 0.7 | 1.0 | 0.1 | 0.2 | 0.2 | 0.2 | 0.7 | 1.3 | -18 | 16 | -1.1 | -6.7 | 33.3 | 20.0 | 0 | -2.31 | 50.0 | 37.5 |
Will Thoni
|
- | 6 | 2.0 | 0.2 | 0.3 | 0.0 | 0.2 | 0.0 | 0.2 | 0.0 | 0.5 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Clay Tormey
|
- | 8 | 2.2 | 0.0 | 0.2 | 0.2 | 0.1 | 0.0 | 0.4 | 0.0 | 0.2 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Manu Giamoukis
|
G | 1 | 2.0 | 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