Penn State
2023 Team Stats (1 games)
65.0
PPG
92.0
Opp
-27.0
Margin
34.4%
FG%
33.3%
3P%
85.7%
FT%
32.0
RPG
6.0
APG
10.0
TO
80.2
Pace
Model Outputs
2022-2023
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 → | 1192 (#118) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1341 (#57) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +36.4 (#45) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.501 (#62) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.545 (#144) | NetEff +1.7 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.745 (#30) | AdjNet +9.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.747 (#29) | AdjNet +9.4 |
2023 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-11-10 | @ | UMBC Retrievers | L | 65 - 92 |
2023 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
D. Brown
|
- | 1 | 36.0 | 20.0 | 3.0 | 0.0 | 1.0 | 2.0 | 1.0 | 17.0 | 8.0 | - | - | - | - | 47.1 | 44.4 | 0 | - | 58.8 | 58.8 |
J. Boonyasith
|
- | 1 | 26.0 | 14.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 18.0 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
D. Davis
|
G | 1 | 25.0 | 10.0 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 10.0 | 4.0 | - | - | - | - | 30.0 | 0.0 | 80.0 | - | 41.0 | 30.0 |
J. Gillespie
|
G | 1 | 30.0 | 10.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 | 13.0 | -1.0 | - | - | - | - | 23.1 | 0.0 | 100.0 | - | 33.9 | 23.1 |
Q. Wells
|
- | 1 | 15.0 | 9.0 | 4.0 | 0.0 | 0.0 | 0.0 | 3.0 | 5.0 | 5.0 | - | - | - | - | 80.0 | 100.0 | 0 | - | 90.0 | 90.0 |
M. Picarelli
|
- | 1 | 18.0 | 5.0 | 1.0 | 1.0 | 4.0 | 0.0 | 2.0 | 0.0 | 9.0 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
K. Jones
|
- | 1 | 14.0 | 4.0 | 5.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 10.0 | - | - | - | - | 0.0 | 0 | 100.0 | - | 72.5 | 0.0 |
J. Ware
|
G | 1 | 24.0 | 3.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 3.0 | 5.0 | - | - | - | - | 0.0 | 0 | 75.0 | - | 31.5 | 0.0 |
M. Saxton
|
- | 1 | 5.0 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 3.0 | 0.0 | - | - | - | - | 33.3 | 0.0 | 0 | - | 33.3 | 33.3 |
A. Campbell
|
- | 1 | 9.0 | 2.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 4.0 | - | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
D. Jenkins
|
F | 1 | 25.0 | 2.0 | 4.0 | 1.0 | 0.0 | 0.0 | 1.0 | 6.0 | 0.0 | - | - | - | - | 0.0 | 0.0 | 100.0 | - | 14.5 | 0.0 |
V. Dorm
|
G | 1 | 1.0 | 2.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 2.0 | - | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
J. Battle
|
- | 1 | 5.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | - | 0.0 | 0 | 50.0 | - | 26.6 | 0.0 |
J. Morici
|
G | 1 | 11.0 | 0.0 | 5.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 4.0 | - | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
K. Roper
|
F | 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
Not enough players with both Numbers/Game and RAPM to plot.
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