Pitt.-Bradford
Model Outputs
2025-2026
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 → | 819 (#464) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 589 (#602) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 694 (#728) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -52.3 (#430) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -58.6 (#723) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.031 (#684) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.001 (#586) | NetEff -47.3 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.001 (#719) | AdjNet -56.7 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.001 (#718) | AdjNet -58.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.031 (#723) | AdjO 48.0 | AdjD 86.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.015 (#728) | AdjO 43.8 | AdjD 89.9 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.005 (#726) | 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 → | 0.006 (#727) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 460 (#580) | RD 119 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | @ | Houghton | L | 40 - 114 |
| 2025-11-10 | @ | Keuka | L | 50 - 65 |
| 2025-11-12 | vs | Geneva | L | 27 - 108 |
| 2025-11-15 | vs | Penn College | L | 34 - 77 |
| 2025-11-25 | vs | Alfred | L | 41 - 79 |
| 2025-12-03 | vs | Hilbert | L | 61 - 67 |
| 2026-01-12 | @ | John Carroll | L | 41 - 112 |
| 2026-01-14 | vs | Alfred St. | L | 50 - 70 |
| 2026-01-17 | @ | Carlow | L | 43 - 72 |
| 2026-01-21 | @ | Penn St.-Behrend | L | 39 - 114 |
| 2026-01-24 | vs | Mount Aloysius | L | 57 - 80 |
| 2026-01-28 | vs | Penn St.-Altoona | L | 51 - 89 |
| 2026-01-31 | @ | La Roche | L | 36 - 119 |
| 2026-02-02 | @ | Penn St.-Altoona | L | 53 - 102 |
| 2026-02-04 | @ | Alfred St. | L | 59 - 85 |
| 2026-02-07 | vs | Carlow | L | 66 - 90 |
2026 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Amber Murak | - | 15 | 37.7 | 18.3 | 2.9 | 1.8 | 1.7 | 0.2 | 7.2 | 21.1 | -3.4 | -475 | -26.4 | -89.1 | 31.6 | 20.7 | 64.2 | -4.35 | 39.7 | 36.6 |
| Dalayla Alexander | - | 15 | 35.8 | 12.3 | 5.9 | 3.6 | 3.4 | 0.1 | 5.5 | 14.9 | 4.8 | -418 | -23.2 | -82.8 | 28.3 | 20.9 | 66.1 | -0.07 | 37.0 | 32.5 |
| Ella Gettings | - | 15 | 25.9 | 8.1 | 8.4 | 0.7 | 0.8 | 0.4 | 2.9 | 9.1 | 6.3 | -261 | -13.7 | -69.1 | 36.8 | 33.3 | 58.8 | -0.29 | 40.1 | 37.1 |
| Raquel Sewell | - | 8 | 19.0 | 4.2 | 7.1 | 0.8 | 0.5 | 0.4 | 1.8 | 4.4 | 6.9 | -101 | -10.1 | -44.5 | 31.4 | 0 | 66.7 | -1.51 | 39.6 | 31.4 |
| Amaria Mims | - | 3 | 21.0 | 3.3 | 3.7 | 0.3 | 0.7 | 0.0 | 2.3 | 4.7 | 1.0 | -53 | -17.7 | -58.3 | 28.6 | 0.0 | 66.7 | -2.66 | 32.6 | 28.6 |
| Stacy Sequeira | - | 6 | 28.0 | 3.0 | 3.3 | 0.5 | 0.0 | 0.0 | 4.3 | 6.2 | -3.7 | -229 | -22.9 | -324.4 | 16.2 | 19.0 | 33.3 | -1.08 | 22.7 | 21.6 |
| Abigail Goss | - | 8 | 26.8 | 2.8 | 4.6 | 0.8 | 0.4 | 0.5 | 1.8 | 4.5 | 2.8 | -162 | -14.7 | -188.2 | 22.2 | 9.1 | 55.6 | -1.08 | 27.5 | 23.6 |
| Joy McBean | - | 5 | 14.6 | 1.8 | 0.2 | 0.2 | 0.8 | 0.0 | 1.2 | 2.6 | -0.8 | -37 | -6.2 | -68.6 | 30.8 | 14.3 | 0.0 | 0.65 | 32.4 | 34.6 |
| Molly Cady | - | 15 | 30.9 | 1.5 | 6.0 | 0.8 | 0.7 | 0.6 | 4.0 | 3.9 | 1.7 | -316 | -16.6 | -76.7 | 17.2 | 0.0 | 75.0 | -3.46 | 19.2 | 17.2 |
| Zennette Zigler | - | 12 | 16.3 | 1.0 | 2.1 | 0.0 | 0.5 | 0.2 | 1.2 | 1.6 | 1.1 | -95 | -5.9 | -77.9 | 21.1 | 12.5 | 75.0 | -2.6 | 28.9 | 23.7 |
| Lilly Thuman | - | 6 | 5.2 | 0.3 | 0.2 | 0.0 | 0.3 | 0.0 | 0.2 | 0.5 | 0.2 | - | - | - | 33.3 | 0 | 0 | -1.51 | 33.3 | 33.3 |
| Stephanie Davis | - | 2 | 15.5 | 0.0 | 1.5 | 1.0 | 0.0 | 0.5 | 2.0 | 0.5 | 0.5 | -21 | -10.5 | -37.3 | 0.0 | 0 | 0 | -0.58 | 0.0 | 0.0 |
| Makartnee Mortimer | - | 2 | 28.0 | 0.0 | 5.0 | 1.0 | 0.0 | 0.0 | 4.5 | 1.5 | 0.0 | -86 | -43.0 | -61.6 | 0.0 | 0 | 0 | -2.85 | 0.0 | 0.0 |
| Tekla Loncki | - | 4 | 5.5 | 0.0 | 0.2 | 0.5 | 0.0 | 0.0 | 0.8 | 0.2 | -0.2 | - | - | - | 0.0 | 0 | 0 | -2.97 | 0.0 | 0.0 |
| Juliet Thuman | - | 2 | 4.8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | -0.62 | 0 | 0 |
| Kayleigha Dowell | - | 2 | 15.6 | 0.0 | 1.0 | 1.0 | 0.5 | 1.0 | 1.5 | 1.5 | 0.5 | - | - | - | 0.0 | 0.0 | 0 | -0.75 | 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