Harvard Crimson
2019 Team Stats (4 games)
76.5
PPG
82.0
Opp
-5.5
Margin
42.4%
FG%
34.0%
3P%
73.7%
FT%
36.3
RPG
10.0
APG
15.8
TO
85.2
Pace
Model Outputs
2018-2019
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 → | 1183 (#190) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1240 (#154) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +21.0 (#211) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.205 (#79) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.199 (#90) | AdjNet -12.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.195 (#91) | AdjNet -12.2 |
2019 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2019-01-02 | @ | North Carolina Tar Heels | L | 57 - 77 |
| 2019-02-08 | vs | Columbia Lions | W | 98 - 96 |
| 2019-03-16 | vs | Pennsylvania Quakers | W | 66 - 58 |
| 2019-03-17 | vs | Yale Bulldogs | L | 85 - 97 |
2019 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B. Aiken
|
G | 3 | 38.7 | 33.7 | 4.0 | 3.7 | 1.0 | 0.0 | 3.7 | 21.7 | 17.0 | - | - | - | 46.2 | 35.7 | 91.2 | - | 63.2 | 53.8 |
N. Kirkwood
|
G | 4 | 26.8 | 11.0 | 3.2 | 1.0 | 1.0 | 0.0 | 3.2 | 7.5 | 5.5 | - | - | - | 50.0 | 47.1 | 66.7 | - | 64.8 | 63.3 |
Baker II
|
- | 2 | 27.5 | 8.0 | 6.0 | 1.5 | 2.0 | 3.0 | 0.5 | 5.5 | 14.5 | - | - | - | 45.5 | 25.0 | 66.7 | - | 58.7 | 54.5 |
J. Bassey
|
G | 4 | 28.8 | 7.8 | 7.5 | 1.0 | 0.5 | 0.8 | 2.0 | 6.2 | 9.2 | - | - | - | 48.0 | 12.5 | 60.0 | - | 52.7 | 50.0 |
C. Juzang
|
G | 4 | 34.0 | 7.8 | 2.2 | 1.5 | 0.8 | 0.0 | 2.0 | 6.8 | 3.5 | - | - | - | 29.6 | 29.4 | 83.3 | - | 48.0 | 38.9 |
D. Djuricic
|
F | 4 | 19.0 | 6.2 | 1.8 | 1.2 | 0.0 | 0.2 | 0.5 | 4.5 | 4.5 | - | - | - | 44.4 | 30.0 | 60.0 | - | 55.8 | 52.8 |
C. Lewis
|
F | 4 | 24.5 | 4.8 | 6.0 | 0.2 | 1.0 | 2.2 | 1.0 | 4.2 | 9.0 | 10 | 0.7 | 1.0 | 52.9 | 0 | 33.3 | 0.94 | 51.9 | 52.9 |
K. Catchings
|
- | 3 | 15.3 | 4.3 | 3.7 | 0.0 | 0.7 | 0.0 | 0.3 | 4.0 | 4.3 | -10 | -0.7 | -1.2 | 25.0 | 40.0 | 55.6 | 1.04 | 40.7 | 33.3 |
M. Forbes
|
- | 3 | 8.7 | 2.3 | 0.7 | 0.0 | 0.0 | 0.0 | 0.0 | 1.7 | 1.3 | - | - | - | 60.0 | 0 | 50.0 | - | 59.5 | 60.0 |
R. Haskett
|
G | 4 | 8.8 | 2.2 | 1.0 | 0.8 | 0.0 | 0.0 | 0.5 | 1.5 | 2.0 | - | - | - | 50.0 | 75.0 | 0 | - | 75.0 | 75.0 |
W. Perez
|
F | 1 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
H. Welsh
|
F | 3 | 9.7 | 1.7 | 2.0 | 0.3 | 0.3 | 0.3 | 0.7 | 2.3 | 1.7 | - | - | - | 28.6 | 100.0 | 0 | - | 35.7 | 35.7 |
C. Johnson
|
G | 2 | 11.5 | 1.5 | 1.0 | 1.0 | 0.0 | 0.0 | 2.0 | 4.5 | -3.0 | 44 | 3.7 | 4.3 | 11.1 | 16.7 | 0 | 1.06 | 16.7 | 16.7 |
T. McCarthy
|
G | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -1.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
S. Freedman
|
G | 1 | 10.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 4.0 | 2.0 | -5.0 | - | - | - | 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