Boston University Terriers
2022 Team Stats (5 games)
57.6
PPG
65.2
Opp
-7.6
Margin
41.5%
FG%
33.7%
3P%
67.9%
FT%
31.6
RPG
12.0
APG
17.0
TO
73.3
Pace
Model Outputs
2021-2022
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 → | 875 (#341) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 876 (#355) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +7.9 (#285) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.230 (#275) | - |
2022 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2021-11-24 | vs | Yale Bulldogs | L | 51 - 57 |
| 2021-12-13 | vs | New Hampshire Wildcats | W | 60 - 47 |
| 2021-12-21 | @ | Georgia Tech Yellow Jackets | L | 49 - 78 |
| 2022-03-07 | vs | Army Black Knights | W | 80 - 74 |
| 2022-03-10 | @ | American University Eagles | L | 48 - 70 |
2022 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. Johnson
|
G | 3 | 29.7 | 11.7 | 1.3 | 2.0 | 1.7 | 0.0 | 2.7 | 11.3 | 2.7 | -47 | -2.8 | -16.6 | 35.3 | 33.3 | 100.0 | 0.28 | 46.1 | 38.2 |
C. Weimar
|
F | 5 | 29.6 | 11.6 | 7.6 | 1.6 | 1.2 | 1.0 | 1.4 | 7.6 | 14.0 | - | - | - | 55.3 | 0 | 61.5 | 0.98 | 58.7 | 55.3 |
L. Shean
|
G | 4 | 25.5 | 10.5 | 2.5 | 1.2 | 0.8 | 0.2 | 0.8 | 7.8 | 6.8 | - | - | - | 38.7 | 40.9 | 81.8 | 1.05 | 58.6 | 53.2 |
E. Esposito
|
G | 3 | 30.0 | 9.7 | 3.7 | 2.0 | 1.3 | 0.7 | 2.7 | 10.7 | 4.0 | - | - | - | 40.6 | 20.0 | 50.0 | 0.17 | 44.1 | 43.8 |
A. Giannaros
|
G | 4 | 24.8 | 5.8 | 2.2 | 2.5 | 0.5 | 0.5 | 5.2 | 4.5 | 1.8 | -17 | -0.9 | -5.1 | 50.0 | 37.5 | 100.0 | 0.49 | 60.9 | 58.3 |
M. Durant
|
F | 5 | 25.6 | 5.4 | 5.0 | 1.0 | 0.8 | 1.8 | 2.2 | 3.4 | 8.4 | -5 | -0.2 | -1.1 | 58.8 | 0 | 50.0 | 0.63 | 58.3 | 58.8 |
R. Childs
|
F | 3 | 20.0 | 4.7 | 4.3 | 0.7 | 1.0 | 1.3 | 2.0 | 4.3 | 5.7 | - | - | - | 30.8 | 33.3 | 66.7 | 0.57 | 44.8 | 38.5 |
M. Pina
|
G | 5 | 24.8 | 4.4 | 2.6 | 1.0 | 0.4 | 0.0 | 1.0 | 5.4 | 2.0 | 45 | 2.0 | 14.9 | 25.9 | 30.0 | 66.7 | 0.85 | 38.8 | 37.0 |
A. Larnard
|
G | 3 | 6.0 | 4.0 | 0.7 | 0.0 | 0.0 | 0.0 | 0.7 | 1.7 | 2.3 | - | - | - | 60.0 | 100.0 | 75.0 | 0.52 | 88.8 | 90.0 |
L. Davenport
|
G | 1 | 11.0 | 4.0 | 4.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 | 7.0 | 8 | 1.6 | 7.3 | 50.0 | 0.0 | 100.0 | 0.16 | 69.4 | 50.0 |
C. Tibbitt
|
F | 5 | 10.0 | 2.6 | 1.4 | 0.8 | 0.2 | 0.0 | 0.6 | 2.6 | 1.8 | - | - | - | 46.2 | 20.0 | 0 | 0.45 | 50.0 | 50.0 |
S. Beneventine
|
G | 4 | 16.2 | 2.2 | 1.8 | 2.0 | 0.2 | 0.2 | 1.0 | 2.5 | 3.0 | 5 | 0.3 | 1.2 | 40.0 | 33.3 | 0 | 1.0 | 45.0 | 45.0 |
K. Mingo
|
G | 1 | 12.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 6.0 | -5.0 | - | - | - | 0.0 | 0.0 | 0.0 | -0.51 | 0.0 | 0.0 |
C. Washington
|
G | 1 | 3.0 | 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