Cortland
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 → | 1181 (#9) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1261 (#25) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1215 (#18) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +14.1 (#66) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +8.9 (#220) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.941 (#207) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.943 (#133) | NetEff +21.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.916 (#198) | AdjNet +20.7 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.916 (#201) | AdjNet +20.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.740 (#211) | AdjO 65.9 | AdjD 54.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.752 (#87) | AdjO 60.3 | AdjD 48.1 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.843 (#109) | 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 → | 0.842 (#103) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1354 (#15) | RD 119 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | vs | Rochester (NY) | W | 53 - 48 |
| 2025-11-11 | vs | Scranton | L | 50 - 69 |
| 2025-11-13 | vs | Ithaca | W | 73 - 44 |
| 2025-11-21 | @ | Carnegie Mellon | L | 50 - 54 |
| 2025-11-22 | @ | Wash. & Jeff. | W | 74 - 62 |
| 2026-01-10 | vs | SUNY Oneonta | W | 58 - 42 |
| 2026-01-13 | vs | Buffalo St. | W | 71 - 41 |
| 2026-01-16 | @ | SUNY Potsdam | W | 67 - 37 |
| 2026-01-17 | @ | Plattsburgh St. | W | 58 - 50 |
| 2026-01-20 | @ | Fredonia | L | 0 - 0 |
| 2026-01-23 | vs | SUNY Morrisville | W | 54 - 49 |
| 2026-01-27 | @ | Buffalo St. | W | 78 - 47 |
| 2026-01-30 | @ | SUNY Oneonta | W | 62 - 39 |
| 2026-01-31 | @ | SUNY New Paltz | L | 55 - 57 |
| 2026-02-06 | vs | Plattsburgh St. | W | 54 - 38 |
| 2026-02-07 | vs | SUNY Potsdam | W | 65 - 40 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brooke Tillotson | - | 14 | 26.7 | 10.6 | 4.7 | 1.3 | 1.9 | 0.8 | 1.4 | 8.1 | 9.8 | 87 | 6.2 | 36.3 | 46.9 | 25.9 | 85.4 | 2.44 | 56.5 | 50.0 |
| Joleen Lusk | - | 14 | 25.6 | 10.6 | 7.5 | 1.6 | 0.8 | 2.1 | 2.6 | 9.9 | 10.0 | 85 | 6.1 | 58.2 | 41.7 | 33.3 | 69.8 | 2.07 | 47.2 | 42.8 |
| Jackie Funk | - | 13 | 26.0 | 9.6 | 3.5 | 1.0 | 0.4 | 0.3 | 1.2 | 9.5 | 4.2 | 50 | 4.5 | 27.9 | 36.6 | 27.6 | 82.6 | 2.29 | 47.0 | 43.1 |
| Cadence Nicholas | - | 10 | 15.3 | 7.5 | 2.8 | 0.9 | 0.9 | 0.2 | 2.0 | 5.3 | 5.0 | -5 | -0.8 | -3.6 | 54.7 | 0.0 | 54.8 | 1.1 | 56.3 | 54.7 |
| Sam Dembinsky | - | 14 | 14.8 | 6.1 | 2.6 | 1.1 | 0.6 | 0.1 | 0.9 | 4.4 | 5.1 | -7 | -0.5 | -5.0 | 54.8 | 41.2 | 57.9 | 2.47 | 61.1 | 60.5 |
| Sophie Bissaillon | - | 15 | 22.7 | 5.9 | 4.6 | 0.7 | 0.6 | 0.4 | 1.3 | 3.8 | 7.1 | 32 | 2.3 | 21.8 | 57.9 | 36.4 | 70.4 | 1.16 | 64.6 | 61.4 |
| Kaeli McAnally | - | 9 | 23.8 | 5.8 | 2.2 | 2.8 | 1.2 | 0.0 | 2.0 | 5.2 | 4.8 | 0 | 0.0 | 0.0 | 38.3 | 35.3 | 83.3 | 0.41 | 49.7 | 44.7 |
| Adriana Fontana | - | 6 | 15.5 | 5.0 | 0.7 | 1.0 | 0.5 | 0.0 | 1.0 | 4.8 | 1.3 | 31 | 3.9 | 167.9 | 41.4 | 35.3 | 0.0 | 0.01 | 51.0 | 51.7 |
| Megan Milleville | - | 8 | 7.5 | 3.5 | 1.9 | 0.9 | 0.1 | 0.4 | 0.9 | 3.2 | 2.6 | 27 | 3.9 | 38.1 | 50.0 | 100.0 | 33.3 | 0.24 | 51.2 | 51.9 |
| Sarah Owen | - | 9 | 9.5 | 3.4 | 2.9 | 0.6 | 0.3 | 0.1 | 1.6 | 2.9 | 2.9 | -5 | -0.6 | -12.0 | 38.5 | 14.3 | 90.9 | 0.19 | 50.3 | 40.4 |
| Alex Dembinsky | - | 5 | 11.9 | 3.2 | 1.2 | 0.8 | 0.6 | 0.0 | 0.2 | 2.2 | 3.4 | - | - | - | 45.5 | 44.4 | 100.0 | - | 67.3 | 63.6 |
| Bella Zingoni | - | 14 | 19.4 | 2.8 | 2.1 | 0.9 | 0.9 | 0.2 | 1.0 | 2.4 | 3.6 | 31 | 2.8 | 14.9 | 36.4 | 29.4 | 62.5 | 4.08 | 48.7 | 43.9 |
| Charli Bennett | - | 7 | 4.5 | 1.6 | 1.1 | 0.4 | 0.4 | 0.0 | 0.6 | 0.9 | 2.1 | 12 | 1.7 | 53.6 | 66.7 | 50.0 | 33.3 | 1.29 | 63.7 | 75.0 |
| Abby Sheehan | - | 8 | 7.4 | 1.6 | 0.9 | 0.8 | 0.1 | 0.1 | 0.9 | 2.0 | 0.6 | -6 | -0.8 | -31.4 | 37.5 | 20.0 | 0 | 0.12 | 40.6 | 40.6 |
| Mariah Huss | - | 13 | 18.3 | 1.5 | 2.8 | 1.5 | 0.8 | 0.0 | 1.2 | 1.6 | 3.8 | 55 | 4.2 | 31.6 | 33.3 | 11.1 | 83.3 | 3.55 | 42.3 | 35.7 |
| Kaitlyn Nestor | - | 6 | 4.5 | 0.8 | 0.7 | 0.2 | 0.0 | 0.0 | 0.5 | 0.8 | 0.3 | 8 | 2.0 | 52.3 | 40.0 | 50.0 | 0 | 0.51 | 50.0 | 50.0 |
| Katie Boyd | - | 12 | 7.4 | 0.4 | 0.6 | 0.5 | 0.1 | 0.0 | 0.5 | 0.9 | 0.2 | 18 | 2.0 | 39.0 | 18.2 | 14.3 | 0 | -0.28 | 22.7 | 22.7 |
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