Illinois Tech
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 → | 876 (#432) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 700 (#578) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 741 (#716) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -24.9 (#379) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -27.6 (#660) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.113 (#626) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.019 (#547) | NetEff -26.6 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.019 (#643) | AdjNet -34.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.017 (#641) | AdjNet -34.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.124 (#640) | AdjO 53.2 | AdjD 74.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.127 (#698) | AdjO 44.1 | AdjD 65.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.046 (#698) | 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 → | 0.050 (#701) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 576 (#573) | RD 115 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | vs | Spalding | L | 58 - 70 |
| 2025-11-08 | @ | Principia | L | 47 - 78 |
| 2025-11-15 | @ | Beloit | L | 50 - 62 |
| 2025-11-18 | vs | Eureka | W | 71 - 58 |
| 2025-11-20 | vs | North Park | L | 45 - 69 |
| 2025-11-24 | @ | Rockford | W | 47 - 41 |
| 2025-12-03 | vs | Lakeland | L | 39 - 68 |
| 2025-12-14 | @ | Pomona-Pitzer | L | 29 - 76 |
| 2025-12-16 | @ | Caltech | L | 31 - 53 |
| 2026-01-10 | @ | St. Norbert | L | 50 - 76 |
| 2026-01-14 | vs | Concordia Chicago | L | 56 - 74 |
| 2026-01-17 | vs | Edgewood | L | 41 - 72 |
| 2026-01-21 | vs | Benedictine (IL) | L | 46 - 72 |
| 2026-01-24 | @ | Marian (WI) | L | 47 - 65 |
| 2026-01-28 | @ | Lakeland | L | 33 - 56 |
| 2026-01-31 | vs | Wis. Lutheran | L | 29 - 70 |
| 2026-02-04 | @ | Dominican (IL) | L | 41 - 48 |
| 2026-02-07 | @ | MSOE | L | 43 - 75 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Chloe Churilla | - | 16 | 25.5 | 11.0 | 7.0 | 1.0 | 0.8 | 0.2 | 2.6 | 10.0 | 7.5 | -138 | -7.3 | -32.5 | 38.8 | 0.0 | 62.7 | 1.69 | 44.8 | 38.8 |
| Grace Goodnough | - | 17 | 22.6 | 8.0 | 4.6 | 1.2 | 0.6 | 0.5 | 1.8 | 8.1 | 5.0 | -142 | -7.1 | -36.4 | 44.9 | 0.0 | 60.0 | -3.72 | 46.3 | 44.9 |
| Berit Rusing | - | 18 | 29.8 | 6.7 | 5.5 | 1.8 | 2.6 | 0.2 | 4.3 | 7.8 | 4.7 | -233 | -11.1 | -48.7 | 28.6 | 0.0 | 67.8 | -4.1 | 36.2 | 28.6 |
| Abigail Marino | - | 18 | 28.7 | 5.1 | 1.9 | 1.2 | 1.0 | 0.1 | 3.3 | 5.8 | 0.1 | -296 | -14.1 | -64.7 | 27.6 | 18.0 | 63.2 | -1.68 | 37.4 | 31.9 |
| Camden Joko | - | 18 | 32.6 | 3.8 | 1.7 | 1.4 | 0.8 | 0.0 | 2.1 | 6.6 | -0.9 | -268 | -12.8 | -57.5 | 19.5 | 18.0 | 45.5 | -2.58 | 28.1 | 27.1 |
| Nerea Del Olmo Perez | - | 12 | 10.2 | 3.4 | 1.5 | 0.2 | 0.3 | 0.2 | 1.2 | 4.3 | 0.1 | -7 | -0.5 | -6.9 | 26.9 | 24.1 | 60.0 | 2.38 | 36.3 | 33.7 |
| Halle Williams | - | 18 | 12.6 | 2.8 | 2.2 | 0.4 | 0.5 | 0.2 | 0.8 | 2.5 | 2.8 | -149 | -7.1 | -96.8 | 37.8 | 0 | 64.0 | -1.03 | 44.6 | 37.8 |
| Uma Peters | - | 7 | 9.7 | 2.3 | 0.4 | 0.1 | 0.1 | 0.0 | 0.4 | 3.0 | -0.4 | -11 | -1.1 | -6.9 | 19.0 | 19.0 | 80.0 | -1.41 | 34.5 | 28.6 |
| Miabella Spica | - | 18 | 10.5 | 1.8 | 1.5 | 0.8 | 0.6 | 0.1 | 1.8 | 1.8 | 1.2 | -119 | -5.7 | -64.8 | 36.4 | 50.0 | 50.0 | -1.79 | 40.9 | 37.9 |
| Morgan Applewhite | - | 16 | 8.2 | 1.8 | 2.4 | 0.4 | 0.4 | 0.2 | 0.8 | 2.1 | 2.3 | -66 | -3.5 | -47.6 | 32.4 | 0 | 38.9 | 0.83 | 34.6 | 32.4 |
| Lea Petitjean | - | 13 | 7.8 | 1.7 | 0.9 | 0.2 | 0.0 | 0.1 | 1.2 | 1.3 | 0.4 | -75 | -5.4 | -79.3 | 52.9 | 0.0 | 66.7 | -1.05 | 56.0 | 52.9 |
| Amanda Wang | - | 15 | 14.8 | 1.4 | 0.7 | 0.1 | 0.1 | 0.0 | 0.6 | 3.0 | -1.3 | -155 | -9.1 | -92.2 | 15.6 | 13.2 | 100.0 | -2.81 | 22.9 | 21.1 |
| Lyla Barr | - | 11 | 8.4 | 0.0 | 1.4 | 0.2 | 0.1 | 0.0 | 0.8 | 0.4 | 0.5 | -42 | -3.0 | -432.6 | 0.0 | 0 | 0 | -0.46 | 0.0 | 0.0 |
| Olivia Ikeda | - | 3 | 4.6 | 0.0 | 0.3 | 0.0 | 0.3 | 0.0 | 0.0 | 1.3 | -0.7 | -19 | -6.3 | -359.1 | 0.0 | 0.0 | 0 | -0.34 | 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