Middlebury
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 → | 1155 (#22) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1100 (#142) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1047 (#191) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +9.2 (#99) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +3.5 (#312) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.817 (#295) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.835 (#203) | NetEff +11.4 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.928 (#186) | AdjNet +22.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.930 (#187) | AdjNet +21.9 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.758 (#199) | AdjO 66.9 | AdjD 54.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.601 (#233) | AdjO 59.0 | AdjD 54.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.672 (#240) | 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 → | 0.659 (#253) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1102 (#153) | RD 99 | GP 22 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-14 | @ | Springfield | L | 56 - 58 |
| 2025-11-15 | @ | Rochester (NY) | W | 67 - 62 |
| 2025-11-18 | vs | Norwich | W | 80 - 36 |
| 2025-11-22 | @ | Union (NY) | L | 75 - 82 |
| 2025-11-25 | @ | VTSU Castleton | W | 68 - 40 |
| 2025-11-30 | vs | Oswego St. | W | 50 - 40 |
| 2025-12-02 | vs | Skidmore | W | 62 - 49 |
| 2025-12-29 | @ | Puget Sound | L | 36 - 42 |
| 2025-12-30 | @ | Pacific Lutheran | W | 81 - 49 |
| 2026-01-10 | @ | Wesleyan (CT) | L | 40 - 56 |
| 2026-01-13 | vs | Smith | L | 52 - 65 |
| 2026-01-16 | vs | Connecticut Col. | L | 48 - 57 |
| 2026-01-17 | vs | Tufts | L | 53 - 67 |
| 2026-01-24 | @ | Williams | W | 62 - 51 |
| 2026-01-27 | @ | MIT | L | 48 - 60 |
| 2026-02-01 | vs | Bates | L | 57 - 64 |
| 2026-02-06 | vs | Bowdoin | L | 47 - 75 |
| 2026-02-07 | vs | Colby | W | 57 - 53 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Calie Messina | - | 18 | 30.2 | 10.3 | 3.8 | 1.3 | 1.0 | 0.2 | 1.3 | 10.1 | 5.2 | 32 | 1.6 | 8.8 | 36.5 | 33.6 | 89.5 | 0.72 | 49.1 | 46.7 |
| Islay Moore | - | 18 | 24.0 | 10.3 | 5.4 | 0.7 | 1.3 | 0.6 | 1.7 | 12.1 | 4.5 | 35 | 1.8 | 13.0 | 33.0 | 25.9 | 67.9 | 0.09 | 40.2 | 38.1 |
| Sarah Chenette | - | 18 | 19.9 | 7.4 | 3.7 | 0.9 | 0.6 | 0.0 | 1.4 | 7.7 | 3.5 | -31 | -1.6 | -15.6 | 34.1 | 0.0 | 62.9 | -2.11 | 40.2 | 34.1 |
| Gabby Stuart | - | 18 | 25.9 | 7.3 | 3.4 | 1.4 | 1.9 | 0.3 | 1.7 | 7.6 | 5.3 | 49 | 2.5 | 20.6 | 31.6 | 19.5 | 77.6 | 0.55 | 41.9 | 34.6 |
| Teagan Lind | - | 17 | 21.0 | 7.2 | 2.8 | 1.6 | 1.2 | 0.4 | 1.8 | 7.6 | 3.9 | -76 | -4.0 | -64.0 | 34.6 | 24.4 | 66.7 | -0.75 | 42.6 | 38.8 |
| Molly Keaveney | - | 12 | 12.8 | 4.1 | 2.2 | 0.6 | 0.3 | 0.0 | 1.1 | 3.3 | 2.8 | 61 | 4.7 | 32.4 | 45.0 | 38.5 | 75.0 | 4.54 | 58.7 | 57.5 |
| Catherine Carrafiello | - | 17 | 15.8 | 3.2 | 2.5 | 0.9 | 0.7 | 0.1 | 1.1 | 2.5 | 3.8 | -17 | -0.9 | -6.7 | 55.8 | 0 | 50.0 | 1.44 | 55.9 | 55.8 |
| Keeley Baglio | - | 12 | 6.5 | 2.8 | 0.9 | 0.5 | 0.2 | 0.2 | 0.8 | 2.9 | 0.9 | 41 | 3.2 | 92.5 | 28.6 | 28.6 | 100.0 | -0.08 | 42.4 | 34.3 |
| Margot Newman | - | 17 | 14.6 | 2.7 | 3.1 | 1.1 | 0.8 | 0.2 | 1.1 | 2.8 | 4.0 | -23 | -1.2 | -19.6 | 29.8 | 20.8 | 76.5 | -2.1 | 42.2 | 35.1 |
| Emma Kirck | - | 18 | 21.1 | 2.3 | 3.2 | 1.8 | 0.7 | 0.0 | 1.3 | 2.5 | 4.2 | -8 | -0.4 | -3.0 | 42.2 | 37.5 | 33.3 | -1.86 | 45.3 | 45.6 |
| Brooke Collins | - | 17 | 13.1 | 2.1 | 1.4 | 0.7 | 1.5 | 0.4 | 0.7 | 2.1 | 3.2 | 37 | 1.9 | 28.2 | 41.7 | 0 | 41.7 | -0.93 | 42.4 | 41.7 |
| Frances Doyle | - | 6 | 7.1 | 1.3 | 0.8 | 0.3 | 0.0 | 0.3 | 0.5 | 2.0 | 0.3 | 7 | 1.0 | 141.2 | 33.3 | 0.0 | 0 | -0.65 | 33.3 | 33.3 |
| Meghan McDonald | - | 7 | 3.7 | 1.1 | 0.6 | 0.3 | 0.1 | 0.3 | 0.0 | 1.0 | 1.4 | 19 | 2.1 | 83.4 | 57.1 | 0 | 0 | 0.39 | 57.1 | 57.1 |
| Amanda Hill | - | 8 | 4.8 | 0.5 | 0.5 | 0.1 | 0.1 | 0.0 | 0.6 | 0.5 | 0.1 | 19 | 2.1 | 117.5 | 25.0 | 0 | 50.0 | -1.24 | 34.7 | 25.0 |
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