Ferris St.
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 → | 1312 (#12) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1340 (#9) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1142 (#44) | HCA +75 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +25.0 (#27) | HCA +2.9 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +24.3 (#56) | HCA +3.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.799 (#245) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.835 (#164) | NetEff +12.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.971 (#118) | AdjNet +30.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.974 (#119) | AdjNet +30.9 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.874 (#106) | AdjO 78.6 | AdjD 57.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.811 (#24) | AdjO 78.5 | AdjD 62.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.878 (#44) | 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 → | 0.871 (#41) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1213 (#37) | RD 156 | GP 5 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2026-01-24 | vs | Lake Superior St. | - | Incomplete score |
| 2026-01-26 | vs | Saginaw Valley | - | Incomplete score |
| 2026-01-31 | vs | Wayne St. (MI) | - | Incomplete score |
| 2026-02-02 | vs | Purdue Northwest | - | Incomplete score |
| 2026-02-07 | @ | Wis.-Parkside | - | Incomplete score |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kadyn Blanchard | - | 5 | 26.9 | 20.2 | 6.2 | 4.0 | 2.6 | 0.0 | 1.6 | 14.8 | 16.6 | 143 | 8.4 | 43.4 | 48.6 | 32.3 | 90.5 | 4.98 | 60.7 | 55.4 |
| Mia Riley | - | 5 | 25.7 | 16.0 | 4.2 | 1.8 | 3.4 | 0.4 | 2.6 | 10.4 | 12.8 | 129 | 7.6 | 42.9 | 44.2 | 29.4 | 87.9 | 4.63 | 60.1 | 49.0 |
| Mya Hiram | - | 5 | 23.4 | 13.6 | 7.0 | 3.2 | 2.4 | 0.0 | 2.8 | 10.6 | 12.8 | 105 | 6.2 | 41.0 | 54.7 | 14.3 | 90.0 | 1.88 | 59.2 | 55.7 |
| Emma Schierbeek | - | 5 | 17.6 | 11.2 | 2.4 | 2.2 | 1.2 | 0.8 | 1.0 | 8.6 | 8.2 | 84 | 4.9 | 49.2 | 46.5 | 35.7 | 100.0 | 2.33 | 61.3 | 58.1 |
| Mara Mitchell | - | 5 | 14.8 | 8.4 | 1.8 | 2.0 | 1.4 | 0.0 | 1.0 | 5.8 | 6.8 | 52 | 3.2 | 35.3 | 58.6 | 50.0 | 80.0 | 0.61 | 67.3 | 65.5 |
| Kenzie Garner | - | 2 | 14.0 | 5.0 | 2.0 | 0.5 | 0.5 | 0.0 | 0.5 | 5.0 | 2.5 | 17 | 4.2 | 50.8 | 40.0 | 40.0 | 0 | 2.03 | 50.0 | 50.0 |
| Elle Irwin | - | 5 | 26.3 | 4.4 | 3.8 | 3.4 | 2.4 | 0.6 | 1.0 | 5.2 | 8.4 | 190 | 11.2 | 58.2 | 26.9 | 17.6 | 62.5 | 5.29 | 37.3 | 32.7 |
| Charlotte Miller | - | 5 | 10.9 | 3.4 | 1.0 | 2.0 | 0.8 | 0.0 | 0.6 | 3.0 | 3.6 | 41 | 2.4 | 14.1 | 46.7 | 33.3 | 0 | -1.6 | 56.7 | 56.7 |
| Claire Erickson | - | 5 | 16.9 | 3.4 | 1.8 | 1.4 | 1.6 | 0.4 | 1.2 | 2.0 | 5.4 | -69 | -3.8 | -16.7 | 80.0 | 33.3 | 0 | -0.57 | 85.0 | 85.0 |
| Alyssa Wirth | - | 4 | 7.8 | 3.2 | 2.0 | 1.2 | 0.0 | 0.8 | 0.2 | 2.8 | 4.2 | -17 | -1.5 | -22.6 | 45.5 | 100.0 | 33.3 | -1.36 | 52.8 | 54.5 |
| Melena Glysch | - | 4 | 10.2 | 3.0 | 3.2 | 1.2 | 1.0 | 0.0 | 0.8 | 1.8 | 6.0 | 40 | 2.9 | 47.0 | 57.1 | 33.3 | 50.0 | 2.23 | 62.2 | 64.3 |
| Grace Lyons | - | 3 | 14.7 | 2.3 | 2.3 | 1.7 | 0.3 | 0.3 | 0.3 | 2.3 | 4.3 | 25 | 1.6 | 18.8 | 28.6 | 40.0 | 50.0 | -1.7 | 44.4 | 42.9 |
| Ally Schultz | - | 5 | 8.6 | 0.4 | 1.0 | 0.4 | 1.0 | 0.0 | 0.0 | 1.8 | 1.0 | 23 | 1.4 | 18.4 | 11.1 | 0.0 | 0 | -0.72 | 11.1 | 11.1 |
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